Method and apparatus for wireless communication employing control for confidence metric bandwidth reduction

ABSTRACT

A communication system having a plurality of forward channel communications and a plurality of corresponding reverse channel communications from and to a plurality of mobile users. A plurality of collectors are distributed at macro-diverse locations for receiving reverse channel signals from the users which are processed to yield one or more sequences of data bits as a burst and corresponding initial confidence metrics for each bit. The collectors forward these reverse channel signals including the data bits and corresponding processed confidence metrics to aggregators. The system includes bandwidth control for minimizing backhaul bandwidth from collector to aggregator while maximizing signal quality.

CROSS REFERENCE

This application is a continuation-in-part of application Ser. No.08/866,700 filed on May 30,1997 entitled METHOD AND APPARATUS FORWIRELESS COMMUNICATION EMPLOYING CONFIDENCE METRIC PROCESSING FORBANDWIDTH REDUCTION, assigned to the same assignee as this application.

This application is a continuation-in-part of application Ser. No.08/801,711 filed Feb. 14, 1997 entitled METHOD AND APPARATUS FORWIRELESS COMMUNICATION EMPLOYING AGGREGATION FOR DIGITAL SIGNALS,assigned to the same assignee as this application.

This application is a continuation-in-part of application Ser. No.08/544,913 filed Oct. 18, 1995, now U.S. Pat. No. 5,715,516, entitledMETHOD AND APPARATUS FOR WIRELESS COMMUNICATION EMPLOYING COLLECTORARRAYS, assigned to the same assignee as this application.

This application is a continuation-in-part of application Ser. No.08/634,141 filed Apr. 19, 1996, now U.S. Pat. No. 5,805,576, entitledMETHOD AND APPARATUS FOR TDMA WIRELESS COMMUNICATION EMPLOYING COLLECTORARRAYS FOR RANGE EXTENSION.

BACKGROUND OF THE INVENTION

The present invention relates to the field of two-way wirelesscommunication systems and more specifically to methods and apparatus forcommunication with mobile telephone users (cellular and personalcommunication systems), basic exchange telecommunications radio,wireless data communications, two-way paging and other wireless systems.

Conventional Cellular Systems

Present day cellular mobile telephone systems developed due to a largedemand for mobile services that could not be satisfied by earliersystems. Cellular systems "reuse" frequency within a group of cells toprovide wireless two-way radio frequency (RF) communication to largenumbers of users. Each cell covers a small geographic area andcollectively a group of adjacent cells covers a larger geographicregion. Each cell has a fraction of the total amount of RF spectrumavailable to support cellular users. Cells are of different sizes (forexample, macro-cell or micro-cell) and are generally fixed in capacity.The actual shapes and sizes of cells are complex functions of theterrain, the man-made environment, the quality of communication and theuser capacity required. Cells are connected to each other via land linesor microwave links and to the public-switched telephone network (PSTN)through telephone switches that are adapted for mobile communication.The switches provide for the hand-off of users from cell to cell andthus typically from frequency to frequency as mobile users move betweencells.

In conventional cellular systems, each cell has a base station with RFtransmitters and RF receivers co-sited for transmitting and receivingcommunications to and from cellular users in the cell. The base stationemploys forward RF frequency bands (carriers) to transmit forwardchannel communications to users and employs reverse RF carriers toreceive reverse channel communications from users in the cell.

The forward and reverse channel communications use separate frequencybands so that simultaneous transmissions in both directions arepossible. This operation is referred to as frequency division duplex(FDD) signaling. In time division duplex (TDD) signaling, the forwardand reverse channels take turns using the same frequency band.

The base station in addition to providing RF connectivity to users alsoprovides connectivity to a Mobile Telephone Switching Office (MTSO). Ina typical cellular system, one or more MTSO's will be used over thecovered region. Each MTSO can service a number of base stations andassociated cells in the cellular system and supports switchingoperations for routing calls between other systems (such as the PSTN)and the cellular system or for routing calls within the cellular system.

Base stations are typically controlled from the MTSO by means of a BaseStation Controller (BSC). The BSC assigns RF carriers to support calls,coordinates the handoff of mobile users between base stations, andmonitors and reports on the status of base stations. The number of basestations controlled by a single MTSO depends upon the traffic at eachbase station, the cost of interconnection between the MTSO and the basestations, the topology of the service area and other similar factors.

A handoff between base stations occurs, for example, when a mobile usertravels from a first cell to an adjacent second cell. Handoffs alsooccur to relieve the load on a base station that has exhausted itstraffic-carrying capacity or where poor quality communication isoccurring. The handoff is a communication transfer for a particular userfrom the base station for the first cell to the base station for thesecond cell. During the handoff in conventional cellular systems, theremay be a transfer period of time during which the forward and reversecommunications to the mobile user are severed with the base station forthe first cell and are not established with the second cell.

Conventional cellular implementations employ one of several techniquesto reuse RF bandwidth from cell to cell over the cellular domain. Thepower received from a radio signal diminishes as the distance betweentransmitter and receiver increases. Conventional frequency reusetechniques rely upon power fading to implement reuse plans. In afrequency division multiple access (FDMA) system, a communicationschannel consists of an assigned particular frequency and bandwidth(carrier) for continuous transmission. If a carrier is in use in a givencell, it can only be reused in cells sufficiently separated from thegiven cell so that the reuse site signals do not significantly interferewith the carrier in the given cell. The determination of how far awayreuse sites must be and of what constitutes significant interference areimplementation-specific details.

TDMA Conventional Cellular Architectures

In TDMA systems, time is divided into time slots of a specifiedduration. Time slots are grouped into frames, and the homologous timeslots in each frame are assigned to the same channel. It is commonpractice to refer to the set of homologous time slots over all frames asa time slot. Each logical channel is assigned a time slot or slots on acommon carrier band. The radio transmissions carrying the communicationsover each logical channel are thus discontinuous. The radio transmitteris off during the time slots not allocated to it.

Each separate radio transmission, which should occupy a single timeslot, is called a burst. Each TDMA implementation defines one or moreburst structures. Typically, there are at least two burst structures,namely, a first one for the initial access and synchronization of a userto the system, and a second one for routine communications once a userhas been synchronized. Strict timing must be maintained in TDMA systemsto prevent the bursts comprising one logical channel from interferingwith the bursts comprising other logical channels in the adjacent timeslots.

Space Diversity

Combining signals from a single source that are received at multiplespaced-apart antennas is called space diversity. Micro-diversity is oneform of space diversity that exists when two or more receiving antennasare located in close proximity to each other (within a distance ofseveral meters for example) and where each antenna receives the signalsfrom the single source. In micro-diversity systems, the received signalsfrom the common source are processed and combined to form an improvedquality resultant signal for that single source. Micro-diversity iseffective against Rayleigh or Rician fading or similar disturbances. Theterminology micro-diverse locations means, therefore, the locations ofantennas that are close together and that are only separated enough tobe effective against Rayleigh or Rician fading or similar disturbances.The signal processing for micro-diverse locations can occur at a singlephysical location and hence micro-diversity processing need notadversely impact reverse channel bandwidth requirements.

Macro-diversity is another form of space diversity that exists when twoor more receiving antennas are located far apart from each other (at adistance much greater than several meters, for example, ten kilometers)and where each antenna receives the signals from the single source. Inmacro-diversity systems, the received signals from the single source areprocessed and combined to form an improved quality resultant signal forthat single source. The terminology macro-diversity means that theantennas are far enough apart to have decorrelation between the meansignal levels for signals from the single source. The terminologymacro-diverse locations means, therefore, the locations of antennas thatare far enough apart to achieve that decorrelation. Sincemacro-diversity processing involves forwarding of signals to a commonprocessing location, an adverse impact on channel bandwidth tends toresult from macro-diversity processing.

Shadow Fading

The decorrelation of mean signal levels employed in macro-diversitysystems is due to local variability in the value of signal strengthdiminution to each of the spaced-apart receiving antennas. This localvariability exists on length scales above Rayleigh or Rician fading andis due to terrain effects, signal blocking by structures or vegetation,and any other variability that exists in a particular environment. Thisvariability is referred to as shadowfading. Decorrelation lengths forshadow fading may be as small as length scales just above Rayleighfading length scales (for example, less than a few meters), or may be aslarge as several kilometers.

Signal Quality Enhancements

In order for diversity combining to increase the quality of a signal,some measure of the quality of the input signals must be generated. Oneof the difficult problems in designing space-diversity algorithms isfinding an accurate measure of precombination decision reliability,which can be computed in real-time. While micro-diversity systemsimprove system quality by ameliorating the effects of Rayleigh fading,which is short-term in nature, they are not very effective in combattingshadow fading, which is caused by effects such as an obstruction comingbetween a transmitter and a receiving antenna. While macro-diversitysystems combine received signals from a number of receivers spaced farapart in space to combat shadow fading, in order for macro-diversitycombining to increase the quality of the resulting signal, some measureof the quality of the individual received signals is necessary.

In the above cross-referenced application entitled METHOD AND APPARATUSFOR WIRELESS COMMUNICATION EMPLOYING AGGREGATION FOR DIGITAL SIGNALS, acommunication system is disclosed having a plurality of forward channelcommunications and a plurality of corresponding reverse channelcommunications from and to a plurality of mobile users. A plurality ofcollectors is distributed at macro-diverse locations for receivingreverse channel signals from the users. Each of the collectors typicallyincludes micro-diversity receivers for receiving the reverse channelsignals from users. The collectors forward these reverse channel signalsto the aggregators. The aggregators combine the received signals fromthe macro-diverse collectors. The combining of multiple collectorsignals for the same user that are both macro-diverse and micro-diverseresults in an output bit stream with fewer bit errors.

In one embodiment of that cross-referenced application, themicro-diverse combining occurs in the collectors and the macro-diversecombining occurs in the aggregators. In an alternative embodiment, someor all of the micro-diverse combining occurs along with themacro-diverse combining in the aggregators.

In the aggregation method of the cross-referenced application, thesignals from users received at collector antennas are processed to yieldone or more sequences of bits and corresponding one or more confidencemetrics for each bit. Inputs from the same user through multiplemicro-diverse antennas at each collector are combined to reduce errorsresulting from Rayleigh and similar disturbances. Signals from the sameuser are processed to form sequences of bits and correspondingconfidence metric vectors from multiple macro-diverse collectors. Thesesignals are combined in an aggregator to reduce errors resulting fromshadow fading and similar disturbances. Increasing the number ofconfidence metric bits (that is increasing the amount of bandwidth)tends to increase the quality of signals (particularly weak signals)while reducing the bandwidth available for other uses (hence reducingthe capacity of the system or the quality of other parts of the system).An appropriate balance between reverse channel bandwidth, aggregatedsignal quality and system capacity is required. The aggregator processesthe data from the multiple collectors and combines and decodes theresulting streams to reduce the probability of bit errors. The combiningprocess utilizes the confidence metrics to make a final decision on eachbit. The number of bits of data used in the cross-referenced applicationcan be large and hence there is a need to reduce the amount of dataallocated to confidence metrics.

In accordance with the above background, the communications problemsresulting from interference, noise, fading and other disturbances createa need for improved wireless communication systems which overcome theinterference problems and other limitations of conventional cellularsystems.

SUMMARY OF THE INVENTION

The present invention is a communication system having a plurality offorward channel communications and a plurality of corresponding reversechannel communications from and to a plurality of mobile users. Aplurality of collectors are distributed at macro-diverse locations forreceiving reverse channel signals from the users. The reverse channelsignals from users received at collector antennas are processed to yieldone or more sequences of data bits as a burst and corresponding initialconfidence metrics for each bit where the confidence metrics for theburst form an initial confidence metric vector. The collectors includebandwidth control to forward these reverse channel signals including thedata bits and corresponding processed confidence metrics to aggregatorsusing different bandwidth levels. The higher the signal quality, thelower the bandwidth level and the lower the signal quality, the higherthe bandwidth level. The aggregators combine the multiple collectorsignals for the same user received from the macro-diverse collectors.The combining of multiple collector signals for the same user when thequality of the signals is low results in an output bit stream for theuser with fewer bit errors. The aggregator includes central control forcommanding bandwidth levels to the collectors based upon informationfrom multiple macro-diverse collectors.

The processing of the initial confidence metrics to form processedconfidence metrics is performed with a number of different variationswhich require different bandwidth levels. The initial confidence metricsin the initial confidence metric vector have an initial range, a_(in),represented by an initial number of bits, γ_(in), and are processed toform processed confidence metrics having a processed range, a_(p),represented by a processed number of bits, γ_(p), and which form theprocessed confidence metric vector.

In certain embodiments, the number of processed confidence metrics inthe processed confidence metic vector are fewer than (and therefore canbe sent at a lower bandwidth level) the number of initial confidencemetrics in the initial confidence metic vector. The reduction in thenumber of confidence metrics is achieved by combining two or moreinitial confidence metrics into a single processed confidence metric andin this manner the total number of bits allocated to the processedconfidence metric vector is less than the number .of bits in the initialconfidence metric vector.

In other embodiments, the processed range, a_(p), and the processednumber of bits, γ_(p), are less than the initial range, a_(in), and theinitial number of bits, γ_(in), respectively. The reduction in thenumber of initial confidence metric bits to a fewer number of bits inthe processed confidence metrics causes the total number of bitsallocated to the processed confidence metric vector to be less than (andtherefore can be sent at a lower bandwidth level) the number of bits inthe initial confidence metric vector.

In other embodiments, both the number of confidence metrics and thenumber of bits per confidence metric are reduced to cause the totalnumber of bits allocated to the processed confidence metric vector to beless than (and therefore can be sent at a lower bandwidth level) thenumber of bits in the initial confidence metric vector.

The present invention employs static and dynamic control of channelbandwidth at local and centralized sites. The bandwidth level isincreased to improve the quality of poor signals and is decreased whensignal quality is good to enable the unused bandwidth to be used byother resources.

The foregoing and other objects, features and advantages of theinvention will be apparent from the following detailed description inconjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a communication system for wireless users employingmacro-diversity combining, each user transmitting user signals to aplurality of collectors that in turn forward the user signals withprocessed confidence metrics for each user to an aggregator forcombining.

FIG. 2 depicts further details of the users, plurality of collectors andaggregator for the communication system of FIG. 1.

FIG. 3 depicts a block diagram representation of a collector.

FIG. 4 depicts a block diagram representation of a collector processingunit for processing of confidence metrics.

FIG. 5 depicts a block diagram representation of compression ofconfidence metrics.

FIG. 6 depicts a block diagram representation of an aggregator.

FIG. 7 depicts a detailed representation of an embodiment of theaggregator of FIG. 6.

FIG. 8 depicts a block diagram representation of an aggregatorprocessing unit for processing of confidence metrics.

FIG. 9 depicts a block diagram representation of uncompression ofcompressed confidence metrics.

FIG. 10 depicts a graphic representation of the signal level from acollector for one particular user.

FIG. 11A, FIG. 11B and FIG. 11C depict a graphic representation of thesignal levels from three different collectors for one particular user.

FIGS. 12A, 12B and 12C depict a representation of when the the FIGS.11A, 11B and 11C signals are above an aggregation threshold level.

FIG. 13 depicts a logical OR of signals analogous to the FIGS. 12A, 12Band 12C signals but processed relative to a higher threshold.

FIG. 14 depicts the logical OR of the FIGS. 12A, 12B and 12C signals.

FIG. 15A, FIG. 15B and FIG. 15C depict sections of FIG. 11A, FIG. 11Band FIG. 11C signal levels, respectively.

FIG. 16A, FIG. 16B and FIG. 16C depict sections of FIG. 12A, FIG. 12Band FIG. 12C signal levels, respectively.

FIG. 17 depicts a time-expanded section of FIG. 13.

FIG. 18 depicts a time-expanded section of FIG. 14.

FIG. 19 and FIG. 20 depict representations of multiple zones of the FIG.1 type in a cellular system.

FIG. 21 depicts representations of multiple zones of the FIG. 1 type ina cellular system with users located in subzones.

DETAILED DESCRIPTION

Cellular System--FIG. 1

In FIG. 1, a cellular system is shown having a zone manager 20 thatbroadcasts forward channel (FC) communications from broadcaster 16 tomultiple users 15 including users U1, U2, . . . , UU located within azone 5 designated by the dashed-line triangle. Each of the multipleusers 15 transmits reverse channel (RC) communications to one or more ofmultiple collectors 45 including collectors C1, C2 and C3, which in turnforward the reverse channel communications to aggregator 17 in zonemanager 20.

Each of the users 15 has a receiver antenna for receiving broadcasts onthe forward channel from the broadcaster 16. Also, each of the users 15has a transmitter that transmits on a reverse channel to the collectors45. The collectors 45 are sited at macro-diverse locations relative toeach other within zone 5. Therefore, multiple copies of macro-diversereverse channel communications are received at the aggregator 17 foreach user.

In FIG. 1, the U1 user 15 is typical with forward channel (FC)communication from broadcaster 16, the user-to-collector reverse channelcommunications (^(u/c) RC) to each of the C1, C2 and C3 collectors 45,and the collector-to-aggregator reverse channel communications (^(c/a)RC) for each of the collectors to aggregator 17. The reverse channelcommunications from the U1 user 15 include the user-to-collectorcommunication ^(u/c) RC1 and the collector-to-aggregator communication^(c/a) RC1, the user-to-collector communication ^(u/c) CRC2 and thecollector-to-aggregator communication ^(c/a) RC2 and theuser-to-collector communication ^(u/c) RC3 and thecollector-to-aggregator communication ^(c/a) RC3. Each of the otherusers U2, . . . , UU in FIG. 1 has similar forward and reverse channelcommunications.

The forward and reverse channel communications of FIG. 1 in the presentinvention apply to any digital radio signal system including for exampleTDMA, CDMA, SDMA and FDMA systems. If the digital radio signals of anyparticular system are not inherently burst structured, then arbitraryburst partitions may be used for confidence metric processing inaccordance with the present invention.

Multiple-Collector Configuration--FIG. 2

In FIG. 2, a plurality of collectors 45-1, . . . , 45-Nc, like thecollectors 45 in FIG. 1, each receive reverse channel communicationsfrom users 15-1, . . . , 15-U. For each user 15, the collectors 45-1, .. . , 45-Nc each process the received signals with initial confidencemetrics to generate data bursts, ¹ B_(p), . . . , ^(Nc) B_(p),respectively, and corresponding processed confidence metric vectors ¹CM_(p). . . , ^(Nc) CM_(p), respectively, all representing the samecommunication from the user 15. These communications havemacro-diversity because of the macro distances separating the collectors45 of FIG. 1. These communications include spatially macro-diverse databursts, ¹ B_(p), . . . , ^(Nc) B_(p), and corresponding processedconfidence metric vectors ¹ CM_(p), . . . , ^(Nc) CM_(p) that areforwarded to the aggregator 17 in formatted form designated as ¹ B_(p)/¹ CM_(p) /¹ M/¹ CC, . . . , ^(Nc) B_(p) /^(Nc) CM_(p) /^(Nc) M/^(Nc)CC. The aggregator 17 combines the spatially diverse data bursts ¹B_(p), . . . , ^(Nc) B_(p), and corresponding confidence metric vectors¹ CM_(p), . . . , ^(Nc) CM_(p) to form a final single representation ofthe data burst, B_(f), with a corresponding final confidence metricvector, CM_(f). The aggregator 17 may use the measurement signals ¹ M, .. . , ^(Nc) M and control signals ¹ CC, . . . ^(Nc) CC in selecting orprocessing the data bursts ¹ B_(p), . . . , ^(Nc) B_(p), and/or thecorresponding confidence metric vectors ¹ CM_(p), . . . , ^(Nc) CM_(p).For example, if a particular burst is associated with a poor qualitysignal, the particular burst may be excluded from the aggregation. Thequality of a signal is measured in one example based on the channelmodel attenuation estimate.

In FIG. 2, the collectors 45-1, . . . , 45-Nc include an RF subsystemgroups 41-1, . . . , 41-Nc which have two or more micro-diversityreceive antennas 48-1, . . . , 48-N_(a). The antennas 48-1, . . . ,48-N_(a) each receives the transmitted signals from each one of aplurality of users 15-1, . . . , 15-U. Each representation of a receivedsignal from a single user that is received by the RF subsystem group41-1, . . . , 41-Nc connects in the form of a burst of data to thecorresponding signal processor group 42-1, . . . , 42-Nc. The receiveddata bursts from the antennas 48-1, . . . , 48-N_(a) are represented as¹ B_(r), . . . , ^(Na) B_(r). The signal processor groups 42-1, . . . ,42-Nc processes the plurality of received bursts for a single user toform a single processed bursts, ¹ B_(p), . . . , ^(Nc) B_(p),representing the signals from the single user. The processed bursts, ¹B_(p), . . . , ^(Nc) B_(p), have corresponding confidence metricvectors, ¹ CM_(p), ² CM_(p), . . . , ^(Nc) CM_(p), representing thereliability of each bit of the data bursts. Bach processed burst has thebits β_(p1), β_(p2), . . . , β_(pB) and the processed confidence metricvector, CM_(p), has the corresponding processed confidence metrics_(p1), _(p2), . . . , _(pB). Measurement signals, ¹ M, . . . , ^(Nc) M,are formed that measure the power or other characteristics of thesignal. The processed bursts, the confidence metric vectors, and themeasurements connect to the interface units 46-1, . . . , 46-Nc whichformat those signals and transmit or otherwise connect them as reversechannel signals to the aggregator 17.

In FIG. 2, the signal processor groups 42-1, . . . , 42-Nc receivetiming information that permits collector signals from each collector tobe time synchronized with signals from each of the other collectors. Forexample, each collector has a global positioning system (GPS) receiver(not shown) for receiving a time synchronization signal. Alternatively,or in addition, the zone manager 20 of FIG. 1 can broadcast or otherwisetransmit time synchronization information. The signal processors 42-1, .. . , 42-Nc provide time stamps in collector control signals ¹ CC, . . ., ^(Nc) CC that are forwarded from interface units 46-1, . . . , 46-Ncas part of the reverse channel signals to the aggregator 17.

Collector--FIG. 3

In FIG. 3, a collector 45 is typical of each of the collectors 45 ofFIG. 1 and FIG. 2. In FIG. 3, the collector 45 includes an RF subsystemgroup 41 which has two or more micro-diversity receive antennas 48-1, .. . , 48-N_(a). The antennas 48-1, . . . , 48-N_(a) each receives thetransmitted signals from each one of a plurality of users. Eachrepresentation of a received signal from a single user that is receivedby the RF subsystem group 41 connects in the form of a burst of data tothe signal processor group 42. The received bursts of data from theantennas 48-1, . . . , 48-Ne are represented as ¹ B_(r), . . . , ^(Na)B_(r), respectively, in FIG. 3. The signal processor group 42 processesthe plurality of received bursts for a single user to form a singleprocessed burst, B_(p), representing the signals from the single user.The processed burst, B_(p), has a confidence metric vector, CM,representing the reliability of each bit of the data comprising theprocessed burst, B_(p). Each processed burst has the bits β_(p1),β_(p2), . . . , β_(pB) and the confidence metric vector, CM, has thecorresponding confidence metrics ₁, ₂, . . . , _(B). Measurementsignals, M, are formed that measure the power or other characteristicsof the signal, and control signals, CC, are generated to control theoperations. The processed burst, B_(p), the confidence metric vector,CM_(p), the measurements, M, and the control, CC, connect to theinterface unit 46 which formats those signals and transmits or otherwiseconnects them as reverse channel signals to the aggregator 17 of zonemanager 20 of FIG. 1.

In FIG. 3, the signal processor group 42 receives timing informationthat permits collector signals from each collector to be timesynchronized with signals from each of the other collectors. Forexample, each collector has a global positioning system (GPS) receiver(not shown) for receiving a time synchronization signal. Alternatively,or in addition, the zone manager 20 or some region manager (not shown)of FIG. 1 can broadcast or otherwise transmit time synchronizationinformation. The time stamp is provided in the control code (CC) signalthat is forwarded from interface unit 46 to the aggregator 17 of FIG. 2.

In FIG. 3, the RF subsystem group 41 includes an RF diversity unit 51that receives signals from users 15 on micro-diversity antennas 48-1, .. . , 48-N_(a) and connects to a channelizer/digitizer 52. Thechannelizer isolates signals on individual carriers for processing withan output for each of the carriers N₁, . . . , N_(ic). The digitalsignals from the channelizer/digitizer 52 for one carrier are input tothe signal processor group 42-1 and specifically to a buffer 98. Theaddress unit 99 selects from buffer 98 bursts that correspond toindividual users for processing by micro-combiner 53. The micro-combiner53 outputs processed data bit values in processed burst, B_(p), andassociated confidence metric values in confidence metric vector, CM_(p).The data and metric values from signal processor 42-1 are connecteddirectly to the format unit 43 in interface unit 46.

In FIG. 3, a plurality of signal processors 42-1, . . . , 42-Ni form asignal processor group 42 with one processor for each channel signalfrom the channelizer/digitizer 52. Each signal processor is likeprocessor 42-1 and provides inputs to interface unit 46. The digitalsignals from the channelizer/digitizer 52 for a carrier are input to oneof the signal processors 42-1, . . . , 42-N_(ic) and a correspondingbuffer like buffer 98 in signal processsor 42-1. The data and metricvalues from signal processors 42-1, . . . , 42-Nic are all connecteddirectly to the format unit 43 in interface unit 46 for forwarding to anaggregator.

In FIG. 3, the control 50 performs control functions associated with theother units of the collector and in particular, receives the timesynchronization signal through antenna 97-2 from some timing source. Thecontrol 50 generates a time stamp that is inserted at times into thecontrol code (CC) field by the interface unit 46 so that each one ormore bursts has a time stamp in a collector that is used at theaggregator to time correlate the same bursts from the same user that areprocessed at different collectors.

In FIG. 3, the address unit 99 controls the writing of the signals intobuffer 98 and the reading of the signals from buffer 98. The addressunit 99 is synchronized by coarse timing information from control 50 andby fine timing information from micro-combiner 53.

Further, a signal measurement unit 54 receives signals from the combiner53 to form power or other measurements on the received bursts or on theprocessed signals from the combiner 53 to form a measurement signal, M,that inputs to interface unit 46.

The format unit 43 changes the format of the data and metric values fromthe signal processor group 42 to form signal, B_(p) /CM_(p) /M/CC, andthe format unit 43 connects to the signal transmit unit 44. The transmitunit 44 of collector 45 transmits or otherwise connects the reversechannel user information, B_(p) /CM_(p) /M/CC, to the aggregator 17. Thetransmission medium between the collector 45 and the aggregator 17 canbe land lines, such as wire or optical fiber, or can be RF transmissionusing either in-band or out-of-band RF transmission signals. If thecollector 45 is located at the aggregator 17, then a local bus or otherdirect connection not requiring transmission is employed.

In FIG. 3, the micro-combiner 53 operates with each of the received databursts ¹ B_(r), . . . , ^(Na) B_(r) to form the processed data burst,B_(p), and a corresponding confidence metric vector, CM. The combiningof confidence metrics from micro-diverse antennas at a collector toproduce processed bits of a processed data burst, B_(p), andcorresponding confidence metrics may be accomplished in one embodimentby an integrated multisensor equalization process. In anotherembodiment, the signals from separate antennas may be equalizedindividually and then combined by averaging or other processing of theequalizer confidence metrics.

The processed data burst, B_(p), includes the processed burst bit valuesγ_(p1), β_(p2), . . . , β_(pB) and the resultant confidence metricvector, CM, includes the corresponding confidence metrics ₁, ₂, . . . ,_(B) where B in the subscript is the number of bits in the burst and thenumber of corresponding confidence metrics, one confidence metric foreach bit.

The confidence metric, _(b), is in the form of a number. A largepositive confidence metric value indicates a high confidence that thedata bit is a binary 1. A large negative confidence metric valueindicates a high confidence that the data bit is a binary 0.

Collector Confidence Metric Processing Unit--FIG. 4 And FIG. 5

In FIG. 4, the Collector Confidence Metric Processing unit 49 of FIG. 3is shown in further detail. The confidence metric vectors for a seriesof bursts are input one at a time to the CM input register 61. Eachconfidence metric vector, CM, includes the confidence metrics ₁, ₂, . .. , _(b), . . . , _(B), one for each of the B data bits, β_(p1), β_(p2),. . . , β_(pb), . . . , β_(pB). in a data burst.

Each of the confidence metrics such as typical confidence metric, _(b),corresponding to a data bit, β_(pb), is in the form of an signed number,s_(b) c_(b), where s_(b) is the sign having a -1 or +1 value and c_(b)is the amplitude where 0<c_(b) <α and the amplitude α indicates therange for c_(b). Therefore, each confidence metric, _(b), is representedby a signed number value, s_(b) c_(b), where (-α)<s_(b) c_(b) <(+α). Forγ equal to the number of bits in the amplitude of the confidence metric,α=2.sup.γ. A large positive confidence metric value, +c_(b), indicates ahigh confidence that _(b) is a binary 1. A large negative confidencevalue for -c_(b) indicates a high confidence that _(b) is a binary 0.More generally, the confidence metrics, ₁, ₂, . . . , _(b), . . . , _(B)are represented by the signed numbers s₁ c₁, s₂ c₂, . . . , s_(b) c_(b),. . . , s_(B) c_(B) for the B bits in a data burst.

In one embodiment described, the logical 1 and logical 0 values of thedata bits, β_(p1), β_(p2), . . . , β_(pb), . . . , β_(pB), in a databurst represent the signs s₁, s₂, . . . , s_(b), . . . , s_(B) where a 1for a data bit is positive and a 0 for a data bit is negative. Only thedata bits, β_(p1), β_(p2), . . . , β_(pb), . . . , β_(pB) and confidencemetrics are actually transmitted from the collectors to the aggregator.At the aggregator, the data bits, β_(p1), β_(p2), . . . , β_(pb), . . ., β_(pB) are mapped to the signs s₁, s₂, . . . , s_(b), . . . , s_(B)where a 1 for a data bit is a positive sign and a 0 for a data bit is anegative sign as follows:

    β=0s.sub.b =-1

    β=1s.sub.b =+1

In FIG. 4, the CM processor 62 operates with a number of differentalgorithms to process the initial confidence metrics to form processedconfidence metrics. For example, the processing includes grouping ofconfidence metrics, scaling and quantizing of confidence metricstogether with static and dynamic control of the processing.

In FIG. 4, the CM processor 62 in one grouping embodiment processes theconfidence metrics in groups and, for each group, provides one or moreprocessed confidence metrics. The initial confidence metrics ₁, ₂, . . ., _(b), . . . , _(B) for one data burst are divided into G groups thatinclude the groups G1, G2, . . . , GG that in turn include theconfidence metrics ₁, . . . , _(g1) for group G1; .sub.(g1+1), . . . ,_(g2) ; . . . ; .sub.(gG-1)+1, . . . , _(gG) for group GG. Each of theconfidence metrics in the first group, ₁, . . . , _(g1), is combined toform a single processed confidence metric _(p1). Similarly, the othergroups are processed to form the processed confidence metrics _(p1),_(p2), . . . , _(pi), . . . , _(Pg).

By way of example, and referring to FIG. 5, the confidence metrics ₁, ₂,. . . , _(b), . . . , _(B) for one burst are divided into four groups.The four groups G1, G2, G3 and G4 include the confidence metrics ₁, . .. , _(g1) for group G1; .sub.(g1+1), . . . , _(g2) ; for group G2;.sub.(g2+1) . . . , _(g3) for group G3; and .sub.(g3+1), . . . , _(g4)for group G4. Each of the confidence metrics in the first group, ₁, . .. , _(g1), is combined to form a single processed confidence metric_(p1). Similarly, the four groups are processed to form the fourprocessed confidence metrics _(p1), _(p2), _(p3), _(p4). The processingfor each group is achieved in one embodiment by averaging the confidencemetrics in a group.

The processed confidence metric for the I^(th) group, _(pi), is given bythe average as follows: ##EQU1##

where,

_(k) =k^(th) initial confidence metric

_(pi) =processed confidence metric for the I^(th) group

g(i)+1=beginning confidence metric in group

g(i+1)=ending confidence metric in group

g(i+1)-g(i)=number of confidence metrics in group

By way of example and referring to FIG. 5 for group G1 with g(1) equalto 4, Eq. (2) becomes: ##EQU2##

In the four-group example described, the processing of four groupscauses four processed confidence metrics to replace all (for example,116 in a GSM embodiment) of the initial confidence metrics. In FIG. 4,the input to register 61 is the initial confidence metrics ₁, ₂, . . . ,_(b), . . . , _(B) and the output, after processing in the collector CMprocessor 62, is the processed confidence metrics _(p1), _(p2), . . . ,_(pG) stored in the CM output register 64. In the example where thenumber of groups, G, is four, the four processed confidence metrics are_(p1), _(p2), ₃ and _(p4).

Other grouping embodiments process confidence metrics by using a medianconfidence metric or some N^(th) percentile confidence metric torepresent two or more of the initial confidence metrics. The combiningof groups of confidence metrics substantially reduces the amount of datarequired to represent confidence metrics and hence reduces the amount ofreverse channel information which is propagated and thereby conservesreverse channel bandwidth.

In FIG. 4, the CM store 63 stores control code and information for thealgorithms used to combine the confidence metrics from the inputregister 61 to form the processed confidence metrics in the outputregister 64. In one example described, store 63 determines that theinput metrics will be divided into four groups and causes each group tobe averaged to form one processed confidence metric per group. Othercontrol algorithms are stored in the CM store 63. For example, thenumber of confidence metrics in each group, the group boundaries(overlapping or non-overlapping) and the number of bits per processedconfidence metric can be selected. The combining process is controllableto use algorithms other than averaging (for example using a medianconfidence metric or some N^(th) percentile confidence metric) and thecombining process is controllable to apply one algorithm at one time andanother algorithm at another time. The store 63 is static in oneembodiment and in other embodiments is modified from time to time withinformation over the remote interface 65.

In some embodiments of the present invention, the confidence metrics arescaled and quantized so that each one can be represented by a smallnumber of bits, typically 2 to 4, to conserve transmission bandwidth.Such quantization of the initial confidence metrics tends to have only aminimal adverse impact on the final signals output from the aggregator17 of FIG. 2 if three or more bits are used. By way of comparison,grouping of initial confidence metrics into grouped confidence metricstends to have a greater adverse impact on the final signals output fromthe aggregator 17 of FIG. 2 when the group sizes are one-half orone-quarter of the total number of initial confidence metrics.

A simple quantization scheme is linear quantization, where the range ofconfidence metrics is divided into 2.sup.γ equal-sized bins, and valuesin each bin are represented by a γ-bit value. In FIG. 4, each of theinitial confidence metrics, CM₁, ₂, . . . , _(i), . . . , _(B) has aninitial range, a_(in), represented by an initial number of metric bits,γi_(in) and the collector confidence metric processing unit processesthe initial confidence metrics to form processed confidence metrics,_(p1), _(p2), . . . , _(pG), each having a processed range, a_(p),represented by a processed number of metric bits, γ_(p), where theprocessed number of metric bits, γ_(p) is typically less than theinitial number of metric bits, γ_(in).

Assuming that confidence metrics are processed in unsigned form (sincethe sign information is present in the corresponding data bit valuesthat are also transmitted to the aggregator) the following formula canbe used to perform linear quantization of the confidence metrics:##EQU3##

where:

_(pi) =processed confidence metric as quantized value of _(i)

max₋₋ ₋₋ value=maximum value of _(i)

i=1, 2, . . . , B

ε=small positive value chosen so that the division always produces anumber less than 1.

The floor function maps its argument to the nearest integer less than orequal to the argument. For example, if the maximum confidence metricpossible from the micro combiner is 100, and the desired number of bitsper transmitted confidence metric is 3, the formula is ##EQU4##

Various examples of confidence metric processing using differentgroupings and quantizations are listed in TABLE 1. In TABLE 1, a_(in)represents the range of each of the input confidence metrics, _(i),where i=1, . . . , B, γ_(in) represents the number of binary bits usedto represent a_(in), a_(p) represents the range of each of the outputconfidence metrics, _(pj), where j=1, . . . , G, γ_(p) represents thenumber of binary bits used to represent a_(p), G represents the numberof groups per burst (assuming 116 data bits per burst as is the case ina GSM embodiment), BITS_(G) represents the number of bits per group, andTOT_(CM) represents the total number of bits per burst used for theconfidence metrics of a confidence metric vector for a burst.

                  TABLE 1                                                         ______________________________________                                        EXAMPLE  a.sub.in                                                                             γ.sub.in                                                                       a.sub.p                                                                            γ.sub.p                                                                      G    BITS.sub.G                                                                           TOT.sub.CM                       ______________________________________                                        1        200    8      200  8    116  1      928                              2        200    8      7    3    116  1      348                              3        200    8      200  8    4    29     32                               4        200    8      200  8    2    58     16                               5        200    8      7    3    4    29     12                               ______________________________________                                    

In TABLE 1, Example 1 is the initial unprocessed confidence metric,Examples 2 and 5 employ quantization as set forth in Eq. (4) and Eq. (5)above and Examples 3, 4 and 5 employ grouping. Note that Example 5employs a combination of both grouping and quantization.

The relationship between the performance of confidence metric processingas determined by the quality of the final signals output from theaggregator 17 of FIG. 2 and the total number of bits per burst,TOT_(CM), depends on a number of factors. When the quality of thereceived signals is high, then the quality of the final signals outputfrom the aggregator 17 tends to be high even when the total number ofbits per burst is low. When the quality of the received signals is low,then the quality of the final signals output from the aggregator 17tends to be higher when the total number of confidence metric bits sentper burst is higher. The total number of bits per burst allocated toconfidence metrics affects the capacity of the system as well as thequality of the signals. Higher numbers of bits allocated for confidencemetrics reduces the number of bits available for other purposes such asfor increased numbers of users in the system. In light of this trade offbetween quality and capacity, the performance of the system is enhancedif more confidence metric bits are allocated to improving poorer qualityinitial signals where the improvement is needed than are allocated toimproving higher quality initial signals where the improvement is notneeded.

Aggregator--FIG. 6 and FIG. 7

In FIG. 6, a block diagram representation of the aggregator 17 is shown.The aggregator 17 includes a receive/format group 66 which operates toreceive and format signals transmitted by the signal transmit unit 44 ofcollectors 45 of FIG. 3. The received signals ¹ B_(p) /¹ CM_(p) /¹ M/¹CC, ² B_(p) /² CM_(p) /² M/² CC, . . . , ^(Nc) B₃ /^(Nc) CM_(p) /^(Nc)M/^(Nc) CC, after formatting are connected to the signal processor 67which processes the received signals for macro-diversity combining. Theformat group 66 uses the time stamp and other control code (CC)information to align the signals from different collectors for the sameuser. More specifically, the format unit 66 for each one or more burstscompares and aligns the time stamps from the control fields ¹ CC, ² CC,. . . , ^(Nc) CC so that the corresponding data, confidence metric andmeasurement signals from different collectors, for the same common burstfrom a user are aligned.

In FIG. 7, further details of the signal processor 67 for the aggregator17 of FIG. 6 are shown. The signal processor 67 of FIG. 7 is arepresentation of the processing of burst signals from a single one ofthe users, for example user 15-1 of FIG. 2 and the N_(c) representationsof the reverse channel signal from the user as received through theN_(c) active collectors, such as the collectors 45-1, 45-2, . . . ,45-N_(c) in FIG. 2.

In FIG. 7, the N_(c) data, metric and measurement values at 96 for asingle user include the data and processed confidence metric pairs [¹B_(b), ¹ CM_(p) ], [² B_(b), ² CM_(p) ], . . . , [^(Nc) B_(b), ^(Nc)CM_(p) ] and the measurement values, ¹ M, ² M, . . . , ^(Nc) M. Theprocessed confidence metrics, ¹ CM_(p), ² CM_(p), . . . , ^(Nc) CM_(p)are processed in the aggregator CM processing units 70-1, 70-2, . . . ,70-Nc, respectively, to form the aggregator processed confidencemetrics, ¹ CM_(pp), ² CM_(pp), . . . , ^(Nc) CM_(pp). The aggregatorprocessed confidence metrics, ¹ CM_(pp), ² CM_(pp), . . . , ^(Nc)CM_(pp) together with the data bits, ¹ B_(b), ² B_(b), . . . , ^(Nc)B_(b), at 87 are input to the input selector 93 which selects one ormore aggregator processed confidence metrics and corresponding data bitsfor each of the combiner unit groups 99 including combiner unit groups99-1, . . . , 99-N_(g). The selected aggregator processed confidencemetrics, ¹ CM_(pp), ² CM_(pp), . . . , ^(Nc) CM_(pp) together with thecorresponding selected data bits of bursts ¹ B_(b), ² B_(b), . . . ,^(Nc) B_(b), are input at 88 to macro-diversity combiners likemacro-diversity combiner 73 in combiner unit 99-1.

The combiner unit group 99-1 is typical of the combiner unit groups99-1, . . . , 99-N_(g) and includes the macro-diversity combiner 73,de-interleaver 74, de-convolution unit 75 and block decoder 85. The dataand metric values from the combiner 73 are de-interleaved in thede-interleaver 74 and de-convolved (that is, the convolutional coding isremoved) in de-convolution unit 75. The data and metric outputs from thede-convolution unit 75 connect to the block decoder unit 85 to form theoutput pair 78-1. Specifically, the combiner unit groups 99-1, . . . ,99-Ng provide the output pairs 78-1, . . . , 78-Ng that are input to theoutput selector 95. The output selector 95 selects one of the outputpairs 78-1, . . . , 78-Ng as the final output pair 78 that connects tocommunications network 76 and, ultimately, after connection through thenetwork, to a speech decoder 77 to re-establish a user voice signal thatcorresponds to the user voice signal that was input to the transceiverof the user 15 in FIG. 2.

The FIG. 7 signal processor 67 includes a measurement processor 91 thatreceives the measurement signals ¹ M, ² M, . . . , ^(Nc) M and processesthem to determine which ones or all of the data and metric values areactually used in the macro-diversity combiners 73 in each of thecombiner unit groups 99. As one example, the measurement signals aremeasures of the power of the received bursts and any burst that has apower level that is below a threshold is not selected for furtherprocessing. The selector 93 selects different ones of the data andmetric input pairs as inputs to the macro-diversity combiners 73. TheFIG. 7 signal processor 67 in a simple embodiment does not use themeasurement signals ¹ M, ² M, . . . , ^(Nc) M.

In FIG. 7 and in one embodiment, the measurement processor 91 providesweighting factors ¹ w_(b), ² w_(b), . . . , .sup.α w_(b), . . . , ^(Nc)w_(b) corresponding to the data bits ¹ β_(p), ² β_(p), . . . , ^(Nc)β_(p) of a burst. The weighting factors are used, for example, to weightthe combination of bit values based upon a measurement parameter frommeasurement processor 91.

The data and metric values from the combiners 73 are de-interleaved inthe de-interleavers 74 and de-convolved in de-convolution units 75,respectively. The data and metric outputs from the de-convolution units75 connect to the block decoders 85, respectively, which in turn connectto the output selector 95. The output selector 95 operates, for example,on frame erasure signals from the block decoders 85 which are input tothe erasure select control 94. The erasure select control 94 may inhibitany of the outputs 78-1, . . . , 78-Ng from block decoders 85 from beingselected as the output 78 when a frame erasure signal is present. Whenmore than one of the outputs is available without a frame erasuresignal, the one selected is the one corresponding to a particularmeasurement signal from measurement processor 91. For example, onehaving the highest power level is selected. The block decoders 85connect through output selector 95 to the communications network 76 andultimately after connection through the network to a vocoder 77, tore-establish a voice signal that corresponds to the user voice signalthat was input to the user transceiver.

Aggregator Confidence Metric Processing Unit--FIG. 8 And FIG. 9

In FIG. 8, the aggregator CM processing unit 70 is typical of the CMprocessing units 70-1, 70-2, . . . , 70-N_(c) of FIG. 7. The processedconfidence metric vectors ¹ CM_(p), . . . , CM_(p), . . . , ^(Nc) CM_(p)are input one at a time to the CM input register 61. Each processedconfidence metric vector, CM_(p), includes as an input the processedconfidence metrics _(p1), . . . , _(pG) and produces as an output theoutput confidence metrics _(pp1), . . . , _(ppG). The type of processingperformed in the aggregator CM processing unit of FIG. 8 complements thetype of processing performed in the collector CM processing unit of FIG.4. Specifically, when the confidence metrics have been grouped in thecollector CM processing unit of FIG. 4, the aggregator CM processingunit of FIG. 8 ungroups the confidence metrics.

In FIG. 8, the CM processor 62 in a grouped confidence metric embodimentoperates for each grouped confidence metric to provide ungroupedconfidence metrics, one for each data bit. By way of the FIG. 5 example,and referring to FIG. 5, the initial confidence metrics ₁, ₂, . . . ,_(b), . . . , _(B) for one burst were divided into four groups. In FIG.8 the grouped confidence metric _(p1), is processed to provide theaggregator output confidence metrics ₁, . . . , _(g1) for group G1; thegrouped confidence metric _(p2) is processed to provide the aggregatoroutput confidence metrics .sub.(g1+1) . . . , _(g2) for group G2, thegrouped confidence metric _(p3) is processed to provide the aggregatoroutput confidence metric .sub.(g2+1), . . . , _(g3) for group G3; andthe grouped confidence metrics _(p4) is processed to provide theaggregator output confidence metrics .sub.(g3+1), . . . , _(g4) forgroup G4. The processing for each grouped confidence metric in theaggregator is achieved, in one embodiment, by setting each of aplurality of aggregator output confidence metrics equal to the groupedconfidence metric value for its corresponding group.

In FIG. 8 for the FIG. 9 example, the input to register 61 for each ofthe 1, . . . , N_(c) collectors is the grouped confidence metrics _(p1),_(p2), _(p3) and _(p4) and the output, after processing in the CMprocessor 62, is the aggregator output confidence metrics ₁, ₂, . . . ,_(b), . . . , _(B) stored in the register 64. The aggregator outputconfidence metrics, .sub.(g1+1), ₂, . . . , _(b), . . . , _(B), are nota one-for-one reconstitution of the initial confidence metrics, ₁, ₂, .. . , _(b), . . . , _(B), since the confidence metric processing may belossy in that some information is lost. Notwithstanding the lossyprocessing, overall system operation is enhanced by allowing flexibilityin trade-offs between quality, bandwidth and capacity.

In FIG. 8, the CM store 63 stores control code and information for thealgorithms used to process the grouped confidence metrics from the CMinput register 61 to form the confidence metrics in the CM outputregister 64. In the example described, store 63 determines that theinput of the metrics has been divided into four groups and causes eachconfidence metric of a group to be equal to the average determined inthe CM processing unit 49 of FIG. 4. Other control algorithms are storedin the CM store 63 of FIG. 8 to match the operation of the collector CMprocessing unit of FIG. 4.

Combining Processed Confidence Metrics

The aggregator 17 of FIG. 6 receives a plurality of bursts ¹ B_(p), . .. , B_(p), . . . , ^(Nc) B_(p), representing the reverse channel signalsfor the same particular one of the users 15 and combines them based onquality metrics. Each burst such as typical burst, B_(p), includes databits β_(p1), β_(p2), . . . , β_(pb), . . . , β_(pB), and a confidencemetric vector, CM, having confidence metrics, ₁, ₂, . . . , _(b), . . ., _(B). The confidence metrics, ₁, ₂, . . . , ₃, . . . , _(B) arerepresented by the signed numbers s₁ c₁, s₂ c₂, . . . , s_(b) c_(b), . .. , s_(B) c_(B). In the embodiment described, the logical 1 and logical0 values of the data bits, β_(p1), β_(p2), . . . , β_(pb), . . . ,β_(pB), in the data burst represent signs s₁, s₂, . . . , s_(b), . . . ,s_(B) of the confidence metrics where a 1 for a data bit is positivesign and a 0 for a data bit is a negative sign.

In an embodiment where N_(c) representations, ¹ β_(pb), ² β_(pb), . . ., ^(Nc) β_(pb), of each bit such as typical bit, β_(pb), are generatedwith Nc confidence metrics, ¹ _(b), ² _(b), . . . , .sup.α_(b), . . . ,^(Nc) _(b) for each bit, each measured by numbers ¹ c_(b), ² c_(b), . .. . , .sup.α c_(b), . . . , ^(Nc) c_(b), respectively, with each number.sup.α c_(b) ranging between 0 and +a and where .sup.α s_(b) is thesign, the average aggregate confidence metric, ^(agg) c_(b) for each bitb is as follows: ##EQU5##

In an example where the number of collectors N_(c) is equal to 3, thecalculations for a single one of the bits b is as follows: ##EQU6## TheEq. (4) confidence metric combining is useful where soft decisioninformation is available for each bit of data. One embodiment forgenerating the initial soft decision information in the form of initialconfidence metrics uses micro-diversity processing at collectors havingtwo or more spatially diverse antennas 48-1, . . . , 48-Na as describedin connection with FIG. 2.

Referring to the collectors of FIG. 3, for example, macro-diversity isachieved with the spatially macro-diverse collectors 45-1, . . . , 45-Ncwhere in an example if N_(c) =3, the collectors are 45-1, 45-2 and 45-3(45-2 and 45-3 are not explicitly shown in FIG. 2). A numerical exampleis as follows:

    a =200

    γ=8

    .sup.1 c.sub.b =103.33 (Collector 45-1), (.sup.1 β.sub.b =0)E.q. (8)

    .sup.2 c.sub.b =56.69 ((Collector 45-2), (.sup.2 β.sub.b =0)

    .sup.3 c.sub.b =166.67 (Collector 45-3), (.sup.3 β.sub.b =1)

The FLOOR function as described in Eq. (4) is applied to the values ofEq. (8) and these values are then forwarded from the collector to theaggregator. At the aggregator, the data bits ¹ β_(b), ² β_(b) and ³β_(b) having values 0, 0 and 1, respectively, are mapped to the signs ¹s_(b), ² s_(b) and ³ s_(b) having values -1, -1 and +1, respectively,and then Eq. (7) becomes: ##EQU7##

In this example, although the magnitude of the negative values forconfidence metrics ¹ c_(b) (-103) for the path 1 (from a collector 45-1of FIG. 2) and ² c_(b) (-56) for path 2 (from a collector 45-2 notexplicitly shown in FIG. 2) indicate a 0 bit, the positive value ofconfidence metric ³ c_(b) for path 3 (from a collector 45-3 notexplicitly shown in FIG. 2) indicates a 1 bit with a magnitude that islarge enough to outweigh the negative magnitudes for confidence metrics¹ c_(b) and ² c_(b).

For the case where micro-diversity equalization occurs at the collectorsand aggregation occurs at an aggregator (where the aggregator isremotely located at a BTS, for example), the number of confidencemetrics and the precision (range) of those metrics is limited in orderto conserve bandwidth. Where the back haul design only allocates a fewbits for transmitting confidence metrics, the number of bits in theinitially formed confidence metrics at the collectors needs to bereduced. For example, if 3-bit integers are allocated for transmittingconfidence metrics, then the range, a, of values transmitted is from 0to 7 (or 1 to 8) where γ indicates the size in bits of the metric andthe range, a, is 2.sup.γ.

Let c_(p) be the magnitude of the processed confidence metric derivedfrom processing the initial confidence metric, c_(in), represented by aγ-bit integer. Then the following algorithm is used to reduce the numberof confidence metric bits required: ##EQU8##

From the previous example with a=200, Eq. (10) becomes for each path##EQU9##

The values of Eq. (11) are transmitted from the collectors to theaggregator. At the aggregator, the data bits ¹ β_(b), ² β_(b) and ³β_(b) having values 0, 0 and 1, respectively, are mapped to the signs ¹s_(b), ² s_(b) and ³ s_(b) having values -1, -1 and +1, respectively,and then Eq. (7) becomes: ##EQU10##

The small negative value determined by Eq. (12) for the processedconfidence metric indicates low confidence that the bit is a 0.

The bit-by-bit confidence metric aggregation is implemented at theaggregator using the 3-bit confidence metric representation with eachdata bit transmitted from the collector. A normal GSM burst has 116coded data bits. Therefore, using 3-bit confidence metrics, anadditional 348 bits of confidence metric information needs to betransmitted for each burst from each collector. In order to reduce thenumber of confidence metric bits further, in embodiments of theinvention, the confidence metrics are grouped. One processed confidencemetric can be used for different group sizes. For example, one metriccan be used for every half burst of data, for every quarter burst ofdata or for every 4 bits of data. If 3-bit confidence metrics aregrouped on a half burst basis, this requires that each burst transmit anadditional 6 bits of data, 3 additional bits for the confidence metricfor each half of the data segment.

The algorithm for forming one grouped confidence metric, c_(pg), for agroup of n confidence metrics and then aggregating is as follows. Theprocessed grouped confidence metric, c_(pg), for a group of n confidencemetrics for a corresponding n data bits, with the bit number for a groupindicated by the subscript, k, is given by averaging the confidencemetrics of the group as follows: ##EQU11## For example, for a groupingof confidence metrics for four data bits ##EQU12## Eq. (13) becomes:##EQU13##

The grouped values of Eq. (15) are transmitted from the three differentcollectors 45 to an aggregator 17. The aggregator performs theungrouping by assigning the group value to each of the ungrouped values,one for each data bit, of a group. The signals are then aggregated, on abit by bit basis, using voting that is weighted by the grouped metricsaccording to Eq. (7) as follows: ##EQU14##

If grouping is done on a half burst basis using 3-bit integers for theconfidence metric, Eq. (13) is as follows: ##EQU15## Weighted Averaging

In an embodiment where N_(c) representations, ¹ β_(pb), ² β_(pb), . . ., ^(Nc) β_(pb), of each bit are generated with confidence metrics,.sup._(b), ² _(b), . . . , ^(Nc) _(b), each measured by numbers ¹ s_(b)¹ c_(b), ² s_(b) ² c_(b), . . . , ^(Nc) s_(b) ^(Nc) c_(b), respectively,with each number .sup.α s_(b) .sup.α c_(b) ranging between (-a) and (+a)and with the weighting values, .sup.α w_(b) for each bit b, the averageaggregate confidence metric, ^(agg) c_(b) for each bit b, is as follows:##EQU16## Non-linear Quantizing

Alternative methods for scaling and quantizing from initial values ofγ_(in) -bits for each initial confidence metric reduced to γ_(p) -bitsfor each processed confidence metric take advantage of the nature of thedistributions of confidence metric magnitudes for good bits versus badbits.

One non-linear method of quantization is a logarithmic mapping functionwhere the following logarithmic mapping function is an example:##EQU17##

The mapping of Eq. (19) achieves the same degree of compression as thelinear mapping, but the aggregation gain is larger for Eq. (19). Eq.(19) has the advantage that less information is sent for the high end ofthe range where there is less chance of confusing good bits with bad.

Bandwidth Control

Bandwidth control of collector-to-aggregator reverse channelcommunications is important for overall system efficiency and isimplemented in both static and dynamic embodiments. The embodiment usedis a function of the system environment considering many factorsincluding the number and density of users, the relative locations ofusers, collectors and aggregators, the physical environment includingthe terrain, buildings and other signal interferers and the dynamicsunder which the system is undergoing change from moment to moment. Thebandwidth control functions are implemented at both collectors and ataggregators and are also implemented at zone and region managers. Theconditions for bandwidth control are implemented by storage ofparameters and algorithms in either or both local storage (CM store 63of FIG. 4) and central storage (CM store 63 of FIG. 8).

In the simplest embodiments, static bandwidth control is implementedwhere the system is tuned for the desired bandwidth operation withoutneed for dynamic changes. Static bandwidth control is useful for examplewhere relatively poor signal quality exists widely so that high ormaximum confidence metric bandwidth is always employed to achieveacceptable signal quality in a poor transmission environment. In anotherembodiment, static bandwidth control is useful for example where thepremium is on maximum signal quality irrespective of the bandwidthrequirements.

Where capacity, quality, bandwidth and cost are interrelated parameters,then dynamic bandwidth control is important. Distributed intelligence atthe collectors is useful for bandwidth conservation. Distributedintelligence at collectors includes means for decoding, for checkingparity and other conditions and for setting confidence metric bandwidth.Parity checking of block coded signals such are used in GSM can give areliable objective indication of received signal quality. The systemincluding the collectors operate in various modes including operationsbased only on local collector information and including operations basedupon central information from a central control (at an aggregator forexample).

Centralized intelligence (at an aggregator for example) is important inmany embodiments for bandwidth conservation. Often, a single collectordoes not have access to sufficient local information to make adequatebandwidth decisions. Each of the collectors alone cannot be aware of theperformance of other collectors based only on the information availablelocally irrespective of how much processing power each of the collectorshas. A common condition where one collector does not have adequate localinformation for a particular user occurs when some other particularcollector is receiving a strong enough signal from that user toparticularly enable acceptable quality to be achieved solely with theinformation from that collector without aggregation of signals from thatone collector or from other collectors. Centralized information in thisexample is effective in allocating bandwidth among the macro-diversecollectors by causing the particular collector to be active and allother collectors to be inactive or operative in low bandwidth modes.

Large bandwidth savings are attained using centralized controlinformation gathered from multiple macro-diverse collectors. Thecentralized control information is used to dynamically control theamount of confidence metric information transmitted by the macro-diversecollectors. The dynamic control is implemented using bandwidth controlmessages (over a control link between the centralized aggregator and thedistributed collectors) that commands the collectors to differentbandwidth modes based upon centralized information and based upon localinformation. In one embodiment, an LAPD-M link implemented in a T1wireline connection can be used for the bandwidth control messagechannel although the faster the control message link, the better thesystem performance. A point-to-point radio T1 link is an example of alower latency connection than a wireline connection.

In one embodiment, communications between collectors and aggregatorsindicate the format of each returned burst in a 4-bit code word. Anexample encoding appropriate for a GSM embodiment has the 4 bits (3, 2,1, 0) split into two 2-bit fields (xx, yy) in TABLE 2 as follows:

                  TABLE 2                                                         ______________________________________                                        Field 1: Grouping Code (bits 3 and 2)                                         xx=00  0 = off mode (send nothing, not even data bits)                        xx=01  1 = group each burst into 2 groups                                     xx=10  2 = group each burst into 4 groups                                     xx=11  3 = N groups, each confidence metric is sent individually              Field 2: Quantization Code (bits 1 and 0)                                     yy=00  0 = 2 bit non-linear quantization                                      yy=01  1 = 3 bit linear quantization                                          yy=10  2 = 3 bit non-linear quantization                                      yy=11  3 = 8 bit linear quantization                                          ______________________________________                                    

Various different bandwidth modes are available for each collectorextending from full off (xx=00) to a range including, for example,minimum (xx=01), intermediate (xx=10) and maximum (xx=11) bandwidthlevels. In the full off mode, neither data bits nor confidence metricsare sent back from a collector to the aggregator. In all other modes, atleast the data bits are sent back and often one or more confidencemetric bits are sent back. In addition to the Grouping Code (xx), therange of each confidence metric is determined by the Quantization Code(yy). These different modes are selected to keep quality acceptablewhile also reducing the bandwidth utilized in order to conservebandwidth. The bandwidth not used for data bits and confidence metricsis available for other uses such as increased capacity of the system orincreased quality for other parts of the system. Backhaul bandwidth froma collector is shared by all users serviced by that collector, soreducing the bandwidth required for some users allows more users toshare a particular communications link.

An example of the usefulness of dynamic centralized control is apparentwhen a collector that has been receiving a strong signal for a user,without need for aggregation of signals from other collectors for thatuser, suddenly no longer can service the needs of the user alone withoutunacceptable quality deterioration. The dynamic bandwidth control sensesthe reduced quality and switches the mode of operation, for example,from a single collector operation without aggregation to a multiplecollector operation where the signals from multiple collectors arecombined for a single user. If required, one or more of the multiplecollectors are also set to increased confidence metric bandwidth levelsin order to compensate for the quality deterioration of the singlecollector initially active or to compensate for the qualitydeterioration of all the collectors, in addition to the initially activecollector, that become active for that user.

An advantage of having the redundant collectors operate in a minimumbandwidth mode, such as one of the grouping modes requiring a smallnumber of bits, rather than a full off mode, is that when one activecollector no longer receives a strong enough signal to maintainacceptable quality, the aggregator can respond quickly to combineconfidence metrics from other collectors operating in minimum bandwidthmodes. Although reduced quality may result during the time elapsed whena bandwidth control message is sent and the message-receiving collectorsresponsively are set to a higher bandwidth mode, the signal is not lostaltogether as is likely to occur if no confidence metrics are being sentbecause of operation in a full off mode.

Local Bandwidth Control--FIG. 10

In FIG. 10, the signal strength of an exemplary user signal is plottedas a function of time. The user signal of FIG. 10 may be located near acollector 45 or near an aggregator 17. In the absence of centralized(remote) control, the local control at the collector operates todetermine the bandwidth in the following manner. Referring to FIG. 4,the CM store 63 stores the mode of operation.

In the absence of a central bandwidth command, the collector receivingthe FIG. 10 signal stores a local high threshold value, T_(h), which inthe example describe is at 6 dB, and stores a low threshold value,T_(h), which in FIG. 10 is at -6 dB. When the signal strength (or otherquality measure) is above the high threshold value, T_(h), then adefault minimum bandwidth is set; for example xx=01 and yy=00. In theFIG. 10 example, the high threshold T_(h), is set at about 6. In FIG.10, the signal level is above the high threshold, T_(h), at from aboutTime=1 to about Time=25, from about Time=210 to about Time=260 and fromabout Time=330 to about Time=340. When the signal strength is betweenthe high threshold value, T_(h), and the low threshold value, T_(lh),then a default intermediate bandwidth is set, for example, xx=10 andyy=01. When the signal strength is less than the low threshold value,TU, then the default maximum bandwidth is set, for example xx=11 andyy=11. The foregoing examples are merely by way of illustration as manyvariants of thresholds and default values are possible.

If the control method employed exhibits unwanted control behavior, thenfiltering and other control processing can be introduced. For example,where the rate of state changes is excessive about the lower threshold,a hysteresis mode of operation is selected.

Assuming for example that the local hysteresis mode is activated, CMstore 63 stores an upper hysteresis threshold, T_(uh), and a lowerhysteresis threshold, T_(lh). In the FIG. 10 example, the upperhysteresis threshold, T_(uh), is about -2 and the lower hysteresisthreshold, T_(lh), is about -6. The processing unit 49 in FIG. 4 alsostores a hysteresis toggle bit, H_(tb), that is set and reset as afunction of the processing to eliminate excessive oscillations.

Referring to FIG. 10, when processing commences at Time=0, it is assumedfor purpose of explanation that the hysteresis toggle bit, H_(tb), is inthe reset state, that the signal level is above the lower hysteresisthreshold, T_(lh), and that the confidence metric bandwidth is set to areduced level for conserving bandwidth in the reverse channel. As longas the signal level remains above the lower hysteresis threshold,T_(lh), the CM processor 62 functions to maintain the operation at areduced confidence metric bandwidth level. The algorithm for producingthe particular reduced confidence metric bandwidth is selected from anyone of a number of possibilities such as grouping with different sizegroups, range compression and others.

When the signal value drops below the upper hysteresis threshold,T_(uh), as occurs for example at about Time=45, Time=60 and Time=125 inthe FIG. 10 example, the confidence metric bandwidth is not changed andremains at a previously set reduced bandwidth value.

When the signal value first drops below the lower hysteresis threshold,T_(lh), as occurs for example at about Time=140, the CM processor 62functions to set the operation for a higher confidence metric bandwidthlevel, for example, at the full maximum confidence metric bandwidthlevel. Also at about Time=140, the hysteresis toggle bit, H_(tb), in thereset state is set to the set state. With the hysteresis toggle bit,H_(tb), in the set state, the confidence metric bandwidth value is notswitched to a reduced bandwidth value until the signal strength hasexceeded the upper hysteresis threshold, T_(uh). Specifically, in FIG.10, at about Time=149 when the signal level exceeds the lower hysteresisthreshold, T_(lh), the confidence metric bandwidth is not changed sincethe hysteresis toggle bit, H_(tb), has not been reset so that theconfidence metric bandwidth remains at the full confidence metric value.

When the signal value again exceeds the upper hysteresis threshold,T_(uh), as occurs for example at about Time=210, the CM processor 62functions to set the operation for a reduced confidence metric bandwidthlevel as occurs for example in FIG. 10 at about Time=205. At this timethe hysteresis toggle bit, H_(tb), is reset.

In the FIG. 10 example, the reduced confidence metric value remains setbetween about Time=205 and about Time=260. At about Time=260 when thesignal value again drops below the lower hysteresis threshold, T_(lh),and the hysteresis toggle bit, H_(tb), in the reset state, the CMprocessor 62 functions to set the operation for a higher confidencemetric bandwidth level which remains until about Time=280 when thesignal strength again exceeds the upper hysteresis threshold, T_(uh). Atabout Time=260, the hysteresis toggle bit, H_(tb), is reset and remainsreset until set again at about Time=280.

In the FIG. 10 example, the reduced confidence metric value remains setbetween about Time=280 and about Time=350. At about Time=350 when thesignal value again drops below from about Time=210 to about Time=260,the hysteresis toggle bit, H_(tb), in the reset state, the CM processor62 functions to set the operation for a higher confidence metricbandwidth level which remains until about Time=365 when the signalstrength again exceeds the upper hysteresis threshold, T_(uh). At aboutTime=365, the hysteresis toggle bit, H_(tb), is reset and remains resetin the FIG. 10 example.

Threshold Level Controls

In some embodiments of the invention, a high threshold, T_(h), ispresent for indicating that only reduced confidence metric bandwidthlevels are required. Whenever the signal level is above the highthreshold, T_(h), a collector when enabled for such control, subject topossible overrides from the remote commands, transmits only at a reducedconfidence metric bandwidth level. Increasing and decreasing the valueof the high threshold, T_(h), will increase and decrease the bandwidthused by the system.

The lower hysteresis threshold, T_(lh), and the upper hysteresisthreshold, T_(uh), are set in order to help control the reverse channelbandwidth used for confidence metrics. Raising the lower hysteresisthreshold, T_(lh), increases bandwidth usage since the system willoperate to send full confidence metrics more frequently. Similarly,lowering the lower hysteresis threshold, T_(lh), decreases bandwidthusage since the system will operate to send full confidence metrics lessfrequently.

In some embodiments of the invention, the aggregator sets the thresholdlevels used by different collectors based upon a bandwidth allocationamong multiple collectors in order to tune the system for efficientbandwidth utilization.

Centralized Control Based Upon Multiple Collector Signals--FIG. 11Through FIG. 18

FIG. 11A, FIG. 11B and FIG. 11C depict graphic representations of theuser reverse channel signals from collectors C1, C2 and C3,respectively, for user U2 in FIG. 1, and FIG. 15A, FIG. 15B and FIG. 15Cdepict an expanded time interval between Time indices 70 to 85 of thosegraphic representations. Note that the mean signal level for the C2collector of FIG. 11B is greater than for the C1 collector of FIG. 11Aand the C3 collector of FIG. 11C. This difference in mean signal levelsis primarily due to the location of the U2 user relative to thecollectors C1, C2 and C3. The U2 user is closest to the C2 collector andhence the mean signal strength at the C2 collector is highest. The U2user is farther from the C1 and C3 collectors and hence the mean signalstrength at the C1 and C3 collectors is lower. The signal strength froma user at a particular collector is approximately proportional to 1/D⁴where D is the distance between the user and the particular collector.Using a collector separation of 10 kilometers(km), U2 in the exampledescribed is about 3 km from C2, about 7.5 km from both C1 and C3. Thisarrangement results in mean signal levels -4.5 dB, 11 dB and -4.6 dB,respectively, for collectors C1, C2 and C3 relative to a reference levelof 0 dB, which represents the mean signal strength of a mobile at thecenter of the triangle formed by C1, C2 and C3.

FIG. 12A, FIG. 12B and FIG. 12C depict representations of the FIG. 11A,FIG. 11B and FIG. 11C signals relative to a threshold level which inFIG. 11A, FIG. 11B and FIG. 11C is 0 dB. FIG. 16A, FIG. 16B and FIG. 16Cdepict an expanded time interval between Time indices 70 to 85 of theFIG. 12A, FIG. 12B and FIG. 12C representations. Whenever the FIG. 11A,FIG. 11B and FIG. 11C signals are above 0 or below 0, the FIG. 12A, FIG.12B and FIG. 12C signals are 1 or 0, respectively.

FIG. 13 and FIG. 14 depict logical OR's of the FIG. 12A, FIG. 12B andFIG. 12C type signals and FIG. 17 and FIG. 18 depict expanded timeintervals between Time indices 70 to 85 of the FIG. 13 and FIG. 14representations. FIG. 13 (FIG. 17) depicts a logical OR of signalsanalogous to the signals of FIG. 12A, FIG. 12B and FIG. 12C processedrelative to a threshold higher than 0, for example, 2. FIG. 14 (FIG. 18)depicts a logical OR of the signals of FIG. 12A, FIG. 12B and FIG. 12Cprocessed relative to a threshold of 0. Whenever the FIG. 14 (FIG. 18)signal is a 1, then at least one of the collectors C1, C2 and C3 isreceiving the U2 user signal with sufficient strength so as not torequire the maximum amount of confidence metric information to assuresufficient quality of operation. Therefore, all collectors can becommanded to send less confidence metric information back. In thisexample, the threshold is set at 0 dB, the relative mean signal strengthof a mobile at the center of the triangle. However, depending on theenvironment, the required threshold can be some higher or lower signallevel.

The decision variables in FIG. 12 through FIG. 14 (FIG. 16 through FIG.18) can be set directly by using the signal levels shown in FIG. 11(FIG. 15). In one embodiment, the decision variables are set based onsignal quality, which can be measured using Frame Erasure Rate (FER),that is, block code parity checking, such as is available in the GSMstandard. The signal quality is, on average, a monotonic function of thesignal levels depicted in FIG. 12 through FIG. 14 (FIG. 16 through FIG.18).

If the collector having the strongest signal is not strong enough byitself for acceptable quality, but acceptable quality can be obtainedwith confidence metric combining, then the bandwidth level of theconfidence metrics must be determined. The stronger the signals, theless confidence metric information required and the weaker the signalsthe more confidence metric information required.

If one of the collectors has a very strong signal for a user that farexceeds the level sufficient by itself to assure acceptable quality,then the other collectors are commanded to full off mode in whichneither confidence metrics nor data bits are sent for that user.

If the best one of the collectors has a strong signal for a user thatmarginally exceeds the level sufficient by itself to assure acceptablequality, then the other collectors are commanded to a minimum bandwidthlevel where compressed confidence metrics and data bits are sent forthat user. The advantage of sending at least the data bits and someconfidence metric information is that in the event of signaldeterioration below the acceptable signal threshold for single collectormode operation, the mode is immediately changed to multiple modecombining without any delay that would be incurred by sending messagesback to the collectors. In order to increase the margin of safety, whensignal quality begins to deteriorate in any mode of operation, messagesare sent to change the mode of operation to a higher bandwidth level.Similarly, in order to take advantage of an increasing margin of safety,when signal quality begins to increase in any mode of operation,messages can be sent to change the mode of operation to a lowerbandwidth level.

Whenever the FIG. 13 (FIG. 17) signal is a less than 1, then two or moreof the collectors C1, C2 and C3 are used for receiving the U2 usersignal and these collector signals are combined to assure sufficientquality of operation. FIG. 13 (FIG. 17) depicts a logical OR of signalsanalogous to the signals of FIG. 12A, FIG. 12B and FIG. 12C butprocessed relative to a threshold higher than 0 dB, for example, 5 dB.Whenever the FIG. 13 (FIG. 17) signal is a 1, then at least one of thecollectors C1, C2 and C3 is receiving the U2 user signal with sufficientstrength so as not to require combining multiple collector signals toassure sufficient quality of operation. Whenever the FIG. 13 (FIG. 17)signal is a less than 1, then it is anticipated that the FIG. 14 (FIG.18) signal will shortly also be less than 1 and the system will shortlyrequire more confidence metric information from two or more of thecollectors C1, C2 and C3 to assure sufficient quality of operation. TheFIG. 13 (FIG. 17) signal transitions from 1 lead the FIG. 14 (FIG. 18)transitions from 1 and hence the FIG. 13 (FIG. 17) signal transitionsfrom 1 are used to originate control messages to increase the confidencemetric bandwidth or for signaling full off to be set to on so thatenough information is conveyed to the aggregator to assure that thesignal quality from the collector signals is adequate. Referring to FIG.17 and FIG. 18, a leading 1-to-0 transition commences at about Time=76in FIG. 17 and the corresponding following 1-to-0 transition occurs atabout Time=78 in FIG. 18. The difference in time, T_(a), between theleading and following 1-to-0 transition is about 0.2 seconds in theparticular example of FIG. 17 and FIG. 18.

The difference in threshold levels used to generate the FIG. 13 (FIG.17) and FIG. 14 (FIG. 18) waveforms determines the amount of time thatis available for signaling changes in bandwidth modes of operation. Inone particular embodiment, the messaging time between collectors and theaggregator is set to be less than 0.2 second. In such an embodiment, thethreshold difference between threshold levels used to generate the FIG.13 (FIG. 17) and FIG. 14 (FIG. 18) waveforms is adjusted to insure thatat least a 0.2 second lead time is available from the FIG. 13 (FIG. 17)transitions from 1 before the FIG. 14 (FIG. 18) transitions from 1. Themessaging time and the thresholds are tunable parameters of thecommunication system. In general, a 0.2 second messaging time isadequate for most environments. For example, a vehicle moving at 50kilometers/hour takes about 2 seconds of travel time (calculated byshadow fading spatial correlation statistics where 2 seconds is the timeconstant for a 1/e decay in correlation) before signal levels changeenough to affect signal. Accordingly, 0.2 second messaging times caneasily control changes in the system bandwidth well in advance of fastmoving users.

In some environments, there are instances where spatial decorrelationoccurs very suddenly and the signal quality deteriorates faster than thesystem can respond. In such environments, where the problem occurs atfixed locations in the zone, the locations where these problems occurare detected and are stored in memory. Whenever a user approaches one ofthese locations, the bandwidth is increased to anticipate the need formore confidence metric information to allow the multiple collectoraggregation to maintain acceptable quality. This mode of operationrequires information about the approximate location of the user. Suchlocation information is determined from the timing of training sequencesand the signal strength measurements such as are available in GSM andother protocols. Both signal strength and timing from multiplemacro-diverse collectors are used to perform triangulation. When a: userleaves such a location, the bandwidth is decreased.

In some environments, where signal quality problems occur in a mannerthat can be predicted based upon patterns of changes in user signals,these patterns are stored in memory and the occurrence of these patternsfor a particular user are recognized by comparing the detected userparameters with the patterns stored in memory. Upon detection of amatch, the bandwidth is increased to anticipate the need for moreconfidence metric information to allow the multiple collectoraggregation to maintain acceptable quality. When the increased bandwidthis not needed, the bandwidth is decreased.

Collectors Commanded to full off Mode

A mobile user sending the center of the triangular region of FIG. 1 isreceived at all three collectors C1, C2 and C3 with mean signalstrengths which are assigned a reference value of 0 dB. For the examplepertaining to FIGS. 11 through 14, it is assumed that this mean signallevel is also the lowest level at which the signal can be reliablyaggregated when all collectors send back full confidence metrics. Theobjective is to calculate a distance from any single collector such thatif a mobile is within that distance, its signal is strong enough at thenearest collector that aggregation is not required. First, the signallevel that is required for a particular environment is calculated, ascharacterized by the shadow fading standard deviation and path lossexponent. A constant-level signal that can be reliably aggregated at areference level of 0 dB will be strong enough to process withoutaggregation at 5 dB. Therefore, if the signal is to be above 5 dB morethan 99% of the time, the mean signal level is required to be at 5 dB+2sigma, where sigma is the standard deviation of the log-normal shadowfading. If sigma=8 dB in this environment, that value implies that amean signal level of 21 dB is required. Assuming for purposes of thisexample that the mean path loss in this environment is 1 /D⁴ (a valuetypical for urban cellular radio) the equation for calculating thedistance to meet any particular signal strength criterion is:

    Off-ModeRadius=(CollectorRadius)*10.sup.(-requiredDb/pathLossExponent*10)

In this equation, CollectorRadius is the distance from the center of atriangle of collectors to any collector. If in the example, the sides ofthe triangle in FIG. 1 are 10 km, the distance from any collector that amobile can be to meet the criterion for being in off mode is 1.7 km.Mobile users closer to any collector are expected to be at least 5 dBabove the reference aggregation level more than 99% of the time.

Combined Signals--FIG. 15A, FIG. 15B and FIG. 15C

FIG. 15A, FIG. 15B and FIG. 15C represent an expanded time interval ofFIG. 11A, FIG. 11B and FIG. 11C between Time indices 70 to 85. Duringthis interval, as observed in FIG. 13, the control level is at 0 meaningthat no single collector is adequate. Therefore during this interval,combining of the confidence metrics for the combining for the FIG. 15A,FIG. 15B and FIG. 15C signals is dictated. The results of such combiningare shown in the following TABLE 3 for different modes of confidencemetric bandwidth where the quality of the combined output signal ismeasured by the frame erasure rate (FER).

                  TABLE 3                                                         ______________________________________                                        Individual Collector                                                                           FER                                                          ______________________________________                                        C1               80%                                                          C2               15%                                                          C3               16%                                                          ______________________________________                                        Combined Collectors                                                                            Aggregated FER                                               ______________________________________                                        Full CM           .5%                                                         Grouped CM        3%                                                          Full off {C1 and C3 off}                                                                       15%                                                          ______________________________________                                    

The savings in bandwidth can be appreciated by observing the amount oftime that the FIG. 12A, FIG. 12B and FIG. 12C and the FIG. 13 signalsare less than 1. In TABLE 3, the signal quality (measured by frameerasure rate) allows the system to determine the Least Significantcollector signal (C1) and the Most Significant collector signal (C2) forpurposes of bandwidth control as explained in connection with TABLE 4.

TABLE 4 indicates bandwidth utilization in the system under localcontrol and under central control.

                  TABLE 4                                                         ______________________________________                                        Collector(s)    FIG.   Bandwidth Utilization                                  ______________________________________                                        C1              12A    81.25                                                  C2              12B    29.31                                                  C3              12C    75.25                                                  Average C1, C2 and C3, 61.94                                                  Local Control                                                                 C1, C2 and C3,  13     37.75                                                  Central Control @ 5.2 db                                                      C1, C2 and C3,  14     26.31                                                  Central Control @ 0 db                                                        ______________________________________                                    

In TABLE 4, the Bandwidth Utilization column represents the bandwidthlevel relative to the maximum bandwidth level that is used fortransmission for a single user. These values assume that bandwidthlevels switch between no grouping, 3-bit quantization of the confidencemetric and quarter burst grouping. Thus a 1 value in FIG. 12 representssending about four times as much information as is sent when a 0 valueis present in FIG. 12.

From TABLE 4, it is apparent that if the C1, C2 and C3 collectors eachoperate independently on only locally available information thatcollector C1 will send 81% of the maximum bandwidth level, thatcollector C2 will send 29% of the maximum bandwidth level and thatcollector C3 will send 75% of the maximum bandwidth level so that C1, C2and C3 are on average sending at 61% of the maximum bandwidth level.However, a centralized aggregator using the OR function of FIG. 13 candetermine that all collectors send at an average of 37% of the maximumbandwidth level. If collectors are switched to full off mode rather thanto grouping mode, the savings are even greater but the system is moreapt to be prone to quality deterioration when signal levels changesuddenly.

Algorithms used to control system bandwidth levels rely on varioussystem parameters. One parameter employed is the signal quality of thereceived user reverse channel. One measure of signal quality in GSM orsimilar systems is the frame error rate (FER) and the good frame rate(GFR) where GFR=(1-FER). In TABLE 5, three quality thresholds based onthe GFR are indicated. The T_(decrease) threshold is used to signal adecrease in bandwidth whenever the signal quality is above a GFR of99.8%, the T_(in) crease threshold is used to signal an increase inbandwidth whenever the signal quality is below a GFR of 97% and theT_(full) threshold is used to signal a change to full bandwidth wheneverthe signal quality is below a GFR of 94%.

                  TABLE 5                                                         ______________________________________                                        Quality Threshold                                                                             GFR = (1 - FER)                                               ______________________________________                                        T.sub.decrease  99.8%                                                         T.sub.increase  97%                                                           T.sub.full      94%                                                           ______________________________________                                    

Many different modes of bandwidth control are possible within the scopeof the present invention. Exemplary control code for controlling thevarious modes of operation appears in the following TABLE 6. In TABLE 6,the italicized values of bandwidth levels (such as Local Maximum,Reduced, Local Minimum, Local Intermediate and so forth are selectedwith different values for xx and yy in order to provide suitabledifferent bandwidth levels. Some of the values in TABLE 6 are indicatedby way of examples.

                                      TABLE 6                                     __________________________________________________________________________    COPYRIGHT © 1997 CELLULAR TELECOM, LTD                                __________________________________________________________________________    AT EACH OF MULTIPLE USERS                                                     ♦ For each user,                                                ♦ Transmit user reverse channel signals                         AT EACH OF MULTIPLE COLLECTORS                                                ♦ For each user,                                                ♦ For each collector, receive user signals and process user     signals to form collector                                                     signals (data and confidence metric),                                         ♦ IF confidence metric bandwidth commanded as Central           Bandwidth Level by                                                            central control in aggregator,                                                        ♦ Set Current Bandwidth Level to Central Bandwidth              Level,                                                                        ♦ Go to XMIT                                            ♦ ELSE                                                                  ♦ IF set to Local Hysteresis Mode, then                           ♦ IF signal quality less than lower hysteresis                  threshold, T.sub.lh,                                                            ♦ Set bandwidth level to Local Maximum value,                   ♦ Set hysteresis toggle bit, H.sub.tb                         ♦ ELSE,                                                             ♦ IF hysteresis toggle bit, H.sub.tb set and                    signal quality greater                                                          than upper hysteresis threshold, T.sub.uh,                                    ♦ Set Current Bandwidth Level to Reduced                        value,                                                                        ♦ Reset hysteresis toggle bit, H.sub.tb                       ♦ ELSE,                                                           ♦ Set Current Bandwidth Level to Local                          Maximum value                                                                 ♦ Go to XMIT                                            ♦ ELSE,                                                           ♦ IF signal quality less than lower threshold,                  T.sub.lh,                                                                         ♦ Set Current Bandwidth Level to Local                          Maximum value,                                                            ♦ ELSE,                                                           ♦ IF signal quality greater than high                           threshold, T.sub.h,                                                             ♦ Set Current Bandwidth Level to Local                          Minimum value                                                               ♦ ELSE,                                                           ♦ Set Current Bandwidth Level to Local                          Intermediate value,                                             ♦ XMIT. Transmit collector signals using Current Bandwidth      Level                                                                         ♦ REPEAT                                                        AT SINGLE AGGREGATOR                                                          Determining Collector Signal Quality Module                                   ♦ For each user,                                                ♦ For each collector,                                           ♦ Measure and store collector signal quality,                   ♦ Order collectors according to collector signal quality        rank                                                                          Selecting Participating Collectors Module                                     ♦ For each user,                                                ♦ Select Participating Collectors for user as function of       collector signal quality rank,                                                location or other parameters,                                                 Combining Collector Signals Module                                            ♦ For each user,                                                ♦ Form Combined Signal by combining individual signals from     Participating Collectors                                                      ♦ Determine user location (Using time-of-arrival and other      information from multiple                                                     macro-diverse collectors)                                                     ♦ Process collector signals to form Current Parameters for      user and update History Store                                                 with Current Parameters (such as location and signal patterns),               Centralized Collector Bandwidth Determining Module                            ♦ Create Desired Bandwidth Level list giving desired            confidence metric bandwidth for all users                                     on all backhaul links coming into the aggregator from collectors,             ♦ For each user,                                                ♦ If the signal quality of Individual Signal for a              particular user exceeds high quality                                          threshold, T.sub.qh, at one particular collector of Participating             Collectors and signal                                                         quality is lilely to remain high for some period of time (for example,        particular user                                                               is very close to a particular collector as determined by signal               time-of-arrival and                                                           signal strength),                                                             ♦ Select particular collector as Primary Collector for          particular user and set                                                               Desired Bandwidth Level for Primary Collector to Primary Minimum              value,                                                                        (for example, xx = 10),                                               ♦ Set Desired Bandwidth Level for Other Collectors to           Secondary Minimum                                                                     value, (for example, xx = 00 which is full off mode)                  ♦ Else,                                                         ♦ IF signal quality of Combined Signal from multiple            collectors is greater than a                                                          first intermediate quality threshold, T.sub.decrease (for                     example, if GFR of TABLE                                                      5 is greater than 99.8%) and signal quality is likely to remain               high for some                                                                 period of time (for example, Combined Signal quality has been                 stable and                                                                    above the threshold, T.sub.decrease for a sufficient period of                time),                                                                          ♦ Decrease Desired Bandwidth Level for each of                  Participating Collec-                                                           tors from one Intermediate value (for example, xx = 01, yy =                  11) for all                                                                   Participating Collectors to a lower Intermediate value (for                   example,                                                                      xx = 01, yy = 01),                                                ♦ IF signal quality of Combined Signal from multiple            collectors is less than a                                                             second intermediate quality threshold, T.sub.increase (for                    example, if GFR of TABLE                                                      5 is less than 97%),                                                            ♦ Increase Desired Bandwidth Level for each of                  Participating Collec-                                                           tors from one Intermediate value (for example, xx = 01, yy =                  11) for                                                                       all Participating Collectors to a higher Intermediate value                   (for exam-                                                                    ple, xx = 11, yy = 01),                                           ♦ IF signal quality of Combined Signal is less than a low       quality threshold, T.sub.full                                                         (for example, if GFR of TABLE 5 is less than 94%),                              ♦ Increase Desired Bandwidth Level for all                      Participating Collectors to                                                     Maximum value (for example, xx = 11, yy = 11),                    ♦ IF Current Parameters match Stored Parameters whereby it      is anticipated that                                                                   signal quality of the Combined Signal will become poor (for                   example, where                                                                the location of the user is approaching a location where signal               quality is                                                                    historically known to be poor for users),                                       ♦ Set Desired Bandwidth Level to Stored value                   (for example, xx = 11,                                                          yy = 11 which is maximum bandwidth)                               Adjusting Desired Bandwidth Level Based Upon Available Bandwidth Module       ♦ For each collector,                                           ♦ Determine collector-to-aggregator Total Available             Bandwidth for all users and                                                   determine Total Remaining Bandwidth available,                                ♦ FOR all user backhaul links coming into collector                       ♦ Order all the users by final signal quality at                aggregator,                                                                   ♦ IF based on Desired Bandwidth Level for all                   users, Total Remain-                                                            ing Bandwidth is greater than 0,                                              ♦ Increase the bandwidth allocation (Desired                    Bandwidth                                                                       Level) of those users having signals with the lowest                          aggre-                                                                        gated final signal quality that aren't already at maximum                     bandwidth level,                                                          ♦ IF based on Desired Bandwidth Level for all                   users, Total Remain-                                                            ing Bandwidth is less than 0,                                                 ♦ Decrease the bandwidth allocations (Desired                   Bandwidth                                                                       Level) of users having signals with the highest aggregated                    final signal quality until available bandwidth fits within                    limits                                                                        of link (Total Remaining Bandwidth equals 0)                              ♦ Set Central Bandwidth Level equal to Desired                  Bandwidth Level                                                                 (as increased or decreased based upon available bandwidth)                  ♦ Forward Central Bandwidth Level to                            Participating Collectors,                                           Adjusting Collector Quality Parameters Module                                 ♦ Adjust collector signal quality thresholds and other          bandwidth parameters based, for                                               example, on number of users in the system, available bandwidth,               historical time-of-day                                                        patterns, and facilities availability.                                        ♦ REPEAT                                                        __________________________________________________________________________

Multiple Zone Configurations--FIG. 19 and FIG. 20

In FIG. 19, the zones 5, including the zones 5-1, 5-2, . . . , 5-6, arelike the zone 5 of FIG. 1 and each zone 5 includes users 15 like thosefor zone 5-1. For example, zone 5-2 is adjacent to zone 5-1 and includesa C4 collector 45 that operates together with at least the collectors C1and C2 that operate with zone 5-1.

In FIG. 19, the cellular system is shown having zone managers 20-1, . .. , 20-6 of which zone manager 20-1 is typical. The zone managers havebroadcasters 16-1, . . . , 16-6, where broadcaster 16-1 is typical, thatbroadcast forward channel (FC) communications to multiple users 15 inone or more of the zones 5-1, . . . , 5-6. Each of the users 15transmits reverse channel (RC) communications to one or more of multiplecollectors 45 including collectors C1, C2, C3 and C4, which in turnforward the reverse channel communications to aggregators 17-1, . . . ,17-6, where aggregator 17-1 is typical. The zone managers 20 can belocated at a base station that is configured in a number of differentways. In one configuration, each broadcaster broadcasts forward channelcommunications in a different one of six sectors in six differentfrequency ranges corresponding to the zones 5-1, 5-2, . . . , 5-6. Theusers in the different zones transmit reverse channels on correspondingfrequency ranges to the various collectors operating in their broadcastranges and the collectors in turn forward reverse channel communicationsto a corresponding one of the aggregators 17. In another configuration,all of the zones use the same frequency ranges and no sectorization isemployed and in such an embodiment one or more zone managers may beemployed. In general, regardless of the configuration, some collectorsites are associated with collectors for several zones. For example, C3services users in two zones, 5-1 and 5-2. The backhaul link from C3 tothe aggregator 17-1 is shared by users from zones 5-1 and 5-2.

In order to conserve bandwidth, the confidence metric bandwidth for onezone is at times reduced in order to permit an increase in the bandwidthof another zone where the zones are sharing reverse channelscommunication bandwidth from common associated collectors, likecollectors C1 and C3 in the example described. Control of the algorithmsused in each collector for determining the bandwidth used by eachcollector are stored and executed in the confidence metric processingunit 49 of FIG. 4 and processing unit 70 of FIG. 8. Further, the zonemanager 20 of FIG. 1 communicates with the processing units 49 and 70over the remote interfaces 65 when adjustments, such as for bandwidthbalancing, are required.

In FIG. 19, the region manager 12 controls the bandwidth allocation ofthe zone managers 20-1, . . . , 20-6 for the contiguous regions 5-1, . .. , 5-6 and for other regions 5' which may or may not be contiguous tothe regions 5-1, . . . , 5-6.

In FIG. 20, the zones 5¹, 5², . . . , 5⁷ are each like the zone 5 ofFIG. 19 and form a seven zone cluster. Similarly, in FIG. 20, the zones6¹, 6², . . . , 6⁷ are each like the zone 5 of FIG. 19 and form a secondseven zone cluster. Any number of additional zone clusters may beprovided as necessary to cover any particular region. The region manager12 of FIG. 20 functions to control the bandwidth values of the collectorreverse channels in order to balance the load among the various regionsof FIG. 20 along common backhaul channels. For example, if traffic tendsto move from one particular zone to another zone during a certain time(such as durng a rush hour commute), the bandwidth of the commonbackhaul channel is dynamically allocated so that the zone with highertraffic is allocated more bandwidth.

Subregion Control--FIG. 21

In FIG. 21, a cellular system like that in FIG. 1 is shown having a zonemanager 20 that broadcasts forward channel (FC) communications frombroadcaster 16 to multiple users 15 including users U1, U2, . . . , UUlocated within a zone 5 designated by the dashed-line triangle. Each ofthe multiple users 15 transmits reverse channel (RC) communications toone or more of multiple collectors 45 including collectors C1, C2 andC3, which in turn forward the reverse channel communications toaggregator 17 in zone manager 20.

Each of the users 15 has a receiver antenna for receiving broadcasts onthe forward channel from the broadcaster 16. Also, each of the users 15has a transmitter that transmits on a reverse channel to the collectors45. The collectors 45 are sited at macro-diverse locations relative toeach other within zone 5. Therefore, multiple copies of macro-diversereverse channel communications are received at the aggregator 17 foreach user.

In FIG. 21, the U1 user 15 is typical with forward channel (FC)communication from broadcaster 16, the user-to-collector reverse channelcommunications (^(u/c) RC) to each of the C1, C2 and C3 collectors 45,and the collector-to-aggregator reverse channel communications (^(c/a)RC) for each of the collectors to aggregator 17. The reverse channelcommunications from the U1 user 15 include the user-to-collectorcommunication ^(u/c) RC1 and the collector-to-aggregator communication^(c/a) RC1, the user-to-collector communication ^(u/c) RC2 and thecollector-to-aggregator communication ^(c/a) RC2 and theuser-to-collector communication ^(u/c) RC3 and thecollector-to-aggregator communication ^(c/a) RC3. Each of the otherusers U2, . . . , UU in FIG. 21 has similar forward and reverse channelcommunications.

In FIG. 21, the U1 users 15-1₁, . . . , 15-1_(u1) are all located in asubregion bounded by the collector C1 and the arc 5₁ and hence are inclose proximity to the collector C1. Because of the close proximity, thesignal strength of the reverse channel transmissions from the U1 users15-1₁, . . . , 15-1_(u1) to collector C1 is normally high and can beexpected to require a low confidence metric bandwidth level for highquality reverse channel transmissions. Similarly, the U2 users 15-2₁, .. . , 15-2_(u2) are all located in a subregion bounded by the collectorC2 and the arc 5₂ and hence are in close proximity to the collector C2and the U3 users 15-3₁, . . . , 15-3_(u3) are all located in a subregionbounded by the collector C3 and the arc 5₃ and hence are in closeproximity to the collector C3. Similarly, because of the closeproximity, the signal strength of the reverse channel transmissions fromthe U2 users 15-2₁, . . . , 15-2_(u2) to collector C2 is normally highand can be expected to require a low confidence metric bandwidth levelfor high quality reverse channel transmissions and because of the closeproximity, the signal strength of the reverse channel transmissions fromthe U3 users 15-3₁, . . . , 15-3_(u3) to collector C3 is normally highand can be expected to require a low confidence metric bandwidth levelfor high quality reverse channel transmissions.

In FIG. 21, the central subregion 5_(c) generally bounded by the arcs5₁, 5₂ and 5₃ are relatively far from the collectors C1, C2 and C3 sothat the reverse channel signal strength from all of the UU users 15-U₁,. . . , 15-U_(uU) in this region to each of the collectors C1, C2 and C3is normally weaker than for users closer to the collectors in thesubregions 5₁, 5₂ and 5₃ can be expected to require a higher confidencemetric bandwidth level for high quality reverse channel transmissions.

While the invention has been particularly shown and described withreference to preferred embodiments thereof it will be understood bythose skilled in the art that various changes in form and details may bemade therein without departing from the spirit and scope of theinvention.

What is claimed is:
 1. A communication system having a plurality ofchannels comprising,a plurality of users for transmitting user signalsin user channels, a plurality of macro-diverse collector meansdistributed at macro-diverse locations, each of said collector meansincluding,collector receiver means for receiving said user signals andproviding a plurality of received signals for each of said plurality ofusers, collector processing means for processing said received signalsto form collector signals including sequences of data bits representingthe received signals and including initial confidence metricscorresponding to said data bits for each of said plurality of users,where the initial confidence metrics are represented by an initialnumber of metric bits,said collector processing means includingcollector confidence metric processing means for processing said initialconfidence metrics to form processed confidence metrics having bandwidthvalues, aggregator means for combining said collector signals using saidprocessed confidence metrics from said plurality of macro-diversecollector means for each of said plurality of users to form a finalsequence of data bits representing the user signals for each of saidplurality of users, bandwidth control means for controlling saidbandwidth values.
 2. A communication system having a plurality offorward channel communications and a plurality of corresponding reversechannel communications comprising,a plurality of users in a broadcasterzone,each of said users including user receiver means for receivingdifferent user forward channel signals and including user transmittermeans for broadcasting user reverse channel signals in a user reversechannel, said plurality of users providing a composite signal formed ofa plurality of different user reverse channels, a plurality ofmacro-diverse collector means distributed in proximity to saidbroadcaster zone at macro-diverse locations, each of said collectormeans including,collector receiver means including a plurality ofmicro-diversity receivers each for receiving said user signals andproviding a plurality of micro-diverse received signals for each of saidplurality of users, collector processing means for processing saidreceived signals to form collector signals including sequences of databits representing the received signals and including initial confidencemetrics corresponding to said data bits for each of said plurality ofusers, where the initial confidence metrics are represented by aninitial number of metric bits,said collector processing means includingcollector confidence metric processing means for processing said initialconfidence metrics to form processed confidence metrics having bandwidthvalues, zone manager means including,broadcaster means including abroadcaster transmitter for broadcasting said plurality of user forwardchannel signals over a broadcaster range to said users in saidbroadcaster zone, aggregator means for combining said collector signalsfrom said plurality of macro-diverse collector means for each of saidplurality of users to form a final sequence of data bits, using saidprocessed confidence metrics, representing the user signals for each ofsaid plurality of users,bandwidth control means for controlling saidbandwidth values.
 3. A communication system having a plurality offorward channel communications and a plurality of corresponding reversechannel communications comprising,a plurality of users in a broadcasterzone,each of said users including user receiver means for receivingdifferent user forward channel signals and including user transmittermeans for broadcasting user reverse channel signals in a user reversechannel, said plurality of users providing a composite signal formed ofa plurality of different user reverse channels, a plurality ofmacro-diverse collector means distributed in proximity to saidbroadcaster zone at macro-diverse locations, each of said collectormeans including,collector receiver means including a plurality ofmicro-diversity receivers each for receiving said user signals andproviding a plurality of micro-diverse received signals for each of saidplurality of users, collector processing means for processing saidreceived signals to form collector signals including sequences of databits representing the received signals and including initial confidencemetrics corresponding to said data bits for each of said plurality ofusers, where the initial confidence metrics are represented by aninitial number of metric bits,said collector processing means includingcollector confidence metric processing means for processing said initialconfidence metrics to form processed confidence metrics having bandwidthvalues, broadcaster means including a broadcaster transmitter forbroadcasting said plurality of user forward channel signals over abroadcaster range to said users in said broadcaster zone, control meansfor selecting ones of said plurality of collector means in a collectorgroup for receiving reverse channel signals from particular ones of saidplurality of users, aggregator means for combining said collectorsignals from said plurality of macro-diverse collector means in saidcollector group for each of said particular ones of said plurality ofusers to form a final sequence of data bits, using said processedconfidence metrics, representing the user signals for each of saidparticular ones of said plurality of users,bandwidth control means forcontrolling said bandwidth values.
 4. A communication system having aplurality of forward channel communications and a plurality ofcorresponding reverse channel communications comprising,a plurality ofusers in a plurality of broadcaster zones,each of said users includinguser receiver means for receiving different user forward channel signalsand including user transmitter means for broadcasting user reversechannel signals in a user reverse channel, said plurality of usersproviding a composite signal formed of a plurality of different userreverse channels, a number, N_(bm), of broadcaster means, each includinga broadcaster transmitter for broadcasting said plurality of userforward channel signals over a broadcaster range to said users in one ofsaid broadcaster zones, a number, N_(c), of collector means distributedin proximity to said broadcaster zones at macro-diverse locations wherethe number N_(c), of collector means is greater than the number, N_(bm),of broadcaster means, each of said collector means including,collectorreceiver means including a plurality of micro-diversity receivers eachfor receiving said composite signal and providing a plurality ofmicro-diverse received signals for each of ones of said plurality ofusers,collector processing means for processing said received signals toform collector signals including sequences of data bits representing thereceived signals and including initial confidence metrics correspondingto said data bits for each of said plurality of users, where the initialconfidence metrics are represented by an initial number of metricbits,said collector processing means including collector confidencemetric processing means for processing said initial confidence metricsto form processed confidence metrics having bandwidth values, collectorforwarding means for forwarding said sequences of data bits and saidprocessed confidence metrics as collector signals for each of said onesof said plurality of users, control means for selecting ones of saidplurality of collector means into one or more collector groups, eachcollector group for receiving reverse channel signals from particularones of said plurality of users, aggregator means for combining saidmacro-diverse collector signals for said each one of particular ones ofthe users from said collector means in each of said collector group toform a final sequence of data bits representing the user signals forsaid each one of particular ones of the users,bandwidth control meansfor controlling said bandwidth values.
 5. A communication system havinga plurality of forward channel communications and a plurality ofcorresponding reverse channel communications comprising,a plurality ofusers in a broadcaster zone,each of said users including user receivermeans for receiving different user forward channel signals and includinguser transmitter means for broadcasting user reverse channel signals ina user reverse channel, said plurality of users providing a compositesignal formed of a plurality of different user reverse channels, aplurality of macro-diverse collector means distributed in proximity tosaid broadcaster zone at macro-diverse locations, each of said collectormeans including,collector receiver means including a plurality ofmicro-diversity receivers each for receiving said user signals andproviding a plurality of micro-diverse received signals for each of saidplurality of users, collector processing means for processing saidreceived signals to form collector signals including sequences of databits representing the received signals and including initial confidencemetrics corresponding to said data bits for each of said plurality ofusers, where the initial confidence metrics are represented by aninitial number of metric bits,said collector processing means includingcollector confidence metric processing means for processing said initialconfidence metrics to form processed confidence metrics having bandwidthvalues, broadcaster means including a broadcaster transmitter forbroadcasting said plurality of user forward channel signals over abroadcaster range to said users in said broadcaster zone, control meansfor selecting first ones of said plurality of collector means in a firstcollector group for receiving reverse channel signals from particularfirst ones of said plurality of users and for selecting second ones ofsaid plurality of collector means in a second collector group forreceiving reverse channel signals from particular second ones of saidplurality of users, aggregator means for combining said collector signals from said plurality of macro-diverse collector means in said firstcollector group for each of said first particular ones of said pluralityof users to form a first final sequence of data bits, using saidprocessed confidence metrics, representing the user signals for each ofsaid first particular ones of said plurality of users, for combiningsaid collector signals from said plurality of macro-diverse collectormeans in said second collector group for each of said second particularones of said plurality of users to form a second final sequence of databits, using said processed confidence metrics, representing the usersignals for each of said second particular ones of said plurality ofusers,bandwidth control means for controlling said bandwidth values andfor allocating bandwidth between said first collector group and saidsecond collector group.
 6. The communication system of claim 1, 2, 3, 4or 5 wherein said bandwidth control means is static whereby saidbandwidth values are fixed according to initial setup conditions.
 7. Thecommunication system of claim 1, 2, 3, 4 or 5 wherein said bandwidthcontrol means is dynamic whereby said bandwidth values are modifiedaccording to conditions that change during the operation of saidcommunication system as a function of time.
 8. The communication systemof claim 7 wherein said bandwidth control means includes local bandwidthcontrol means in said collector processing means.
 9. The communicationsystem of claim 7 wherein said bandwidth control means includes centralbandwidth control means in said aggregator means.
 10. The communicationsystem of claim 7 wherein said bandwidth control means includes,for eachof said plurality of macro-diverse collector means, local bandwidthcontrol means for controlling bandwidth levels, central bandwidthcontrol means in said aggregator means receiving information from saidplurality of macro-diverse collector means to provide centralinformation for setting bandwidth levels for said macro-diversecollector means, control channel means connecting said central bandwidthcontrol means to said local bandwidth control means in said plurality ofmacro-diverse collector means for sending said central information tocontrol the bandwidth levels of said macro-diverse collector means. 11.The communication system of claim 10 wherein at each particularmacro-diverse collector means of said plurality of macro-diversecollector means, said local bandwidth control means includes localprocessing means for processing local information at said particularmacro-diverse collector means to set the bandwidth level of saidparticular macro-diverse collector means.
 12. The communication systemof claim 11 wherein said local processing means receives said centralinformation and sets the bandwidth level of said particularmacro-diverse collector means based upon said central information andsaid local information.
 13. The communication system as in claim 12wherein said local information is based on signal quality.
 14. Thecommunication system as in claim 12 wherein said local information isbased on signal quality measured against a plurality of qualitythresholds.
 15. The communication system as in claim 12 wherein saidcentral information is based on current parameters and storedparameters.
 16. The communication system of claim 1 wherein said currentparameters are the location of a user and the stored parameters areknown poor signal quality locations in a zone.
 17. The communicationsystem of claim 10 wherein said central bandwidth control means includesa plurality of modules executable for controlling bandwidth values. 18.The communication system of claim 17 wherein said plurality of modulesinclude a module for determining collector signal quality.
 19. Thecommunication system of claim 17 wherein said plurality of modulesinclude a module for selecting participating collectors.
 20. Thecommunication system of claim 17 wherein said plurality of modulesinclude a module for combining collector signals.
 21. The communicationsystem of claim 17 wherein said plurality of modules include a modulefor centralized determining collector bandwidth.
 22. The communicationsystem of claim 17 wherein said plurality of modules include a modulefor updating collector bandwidth usage.
 23. The communication system ofclaim 17 wherein said plurality of modules include a module foradjusting collector quality parameters.
 24. The communication system ofclaim 7 wherein said bandwidth control means includes,for each of saidplurality of macro-diverse collector means, local bandwidth controlmeans for controlling bandwidth levels, central bandwidth control meansin said aggregator means receiving information from said plurality ofmacro-diverse collector means to provide central information for settingbandwidth levels for said macro-diverse collector means, said centralinformation providing different bandwidth levels for different ones ofsaid macro-diverse collector means , control channel means connectingsaid central bandwidth control means to said local bandwidth controlmeans in said plurality of macro-diverse collector means for sendingsaid central in formation Said aggregator means combining said collectorsignals with said different bandwidth levels.
 25. The communicationsystem of claim 1, 2, 3, 4 or 5 wherein said collector confidence metricprocessing means processes said initial confidence metrics to formprocessed confidence metrics represented by a processed number of metricbits fewer than said initial number of metric bits.
 26. Thecommunication system of claim 1, 2, 3, 4 or 5 wherein said aggregatormeans includes aggregator confidence metric processing means forprocessing said processed confidence metrics to form aggregatorconfidence metrics for each of said data bits.
 27. The communicationsystem of claim 1, 2, 3, 4 or 5 wherein said collector processing meansincludes group processing means for processing said initial confidencemetrics in groups to form said processed confidence metrics as groupedconfidence metrics having grouped numbers of confidence metric bitsfewer than said initial number of metric bits.
 28. The communicationsystem of claim 1, 2, 3, 4 or 5 wherein the initial confidence metricshave an initial range, a_(in), represented by an initial number ofmetric bits, γ_(in), and said collector confidence metric processingmeans includes range processing means for processing the initialconfidence metrics to form processed confidence metrics having aprocessed range, a_(p), represented by a processed number of metricbits, γ_(p), where the processed number of metric bits, γ_(p) is lessthan the initial number of metric bits, γ_(in).
 29. The communicationsystem of claim 1, 2, 3, 4 or 5wherein said collector processing meansincludes group processing means for processing said initial confidencemetrics having an initial range, a_(in), represented by an initialnumber of metric bits, γ_(in), in groups, ₁, . . . , _(G), to formgrouped confidence metrics including the confidence metrics ₁, . . . ,_(g1) for group G1; .sub.(g1+1), . . . , _(g2) ; for group G2; . . . ;.sub.(g3+1), . . . , _(gG) for group GG having grouped numbers ofconfidence metric bits, γ_(g), fewer than said initial number of metricbits, wherein said collector confidence metric processing means includesrange processing means for processing the grouped confidence metricshaving an initial range, a_(in), represented by an initial number ofmetric bits, γ_(in), to form processed confidence metrics having aprocessed range, a_(p), represented by a processed number of metricbits, γ_(p), where the processed number of metric bits, γ_(p) is lessthan the initial number of metric bits, γ_(in), wherein said aggregatormeans includes aggregator confidence metric processing means forprocessing said processed confidence metrics to form aggregatorconfidence metrics for each of said data bits.
 30. The communicationsystem of claim 1, 2, 3, 4 or 5 wherein,said collector receiver meansincludes a plurality of micro-diversity receivers each for receivingsaid user signals and providing a plurality of micro-diverse receivedsignals for each of said plurality of users, said collector processingmeans processes said micro-diverse received signals to form saidcollector signals including sequences of data bits representing themicro-diverse received signals and including said initial confidencemetrics corresponding to said data bits for each of said plurality ofusers.
 31. The communication system of claim 1, 2, 3, 4 or 5 whereinsaid aggregator means receives, from N_(c) of said collector means,N_(c) macro-diverse collector signals each having a processed confidencemetric value, .sup.α c_(b) for each bit and combines said processedconfidence metric values to form an average processed confidence metric,^(agg) c_(b), as follows: ##EQU18## where, ^(agg) c_(b) =averageprocessed confidence metric.sup.α c_(b) =number ranging between (0) and(+a) .sup.α s_(b) =sign N_(c) =number of macro-diverse collectorsignals.
 32. The communication system of claim 1, 2, 3, 4 or 5 whereinsaid aggregator means receives, from N_(c) of said collector means,N_(c) macro-diverse collector signals each having a processed confidencemetric value, .sup.α c_(b) for each bit and each having a weightingfactor, .sup.α w_(b), for each bit and combines said processedconfidence metric values to form a weighted average confidence metric,^(agg) c_(b), as follows: ##EQU19## where, ^(agg) c_(b) =weightedaverage processed confidence metric.sup.α c_(b) =number .sup.α s_(b)=sign N_(c) =number of macro-diverse collector signals .sup.α w_(b)=weighting factor for each bit.
 33. The communication system of claim 1,2, 3, 4 or 5 wherein said user signals employ multiple access protocols.34. The communication system of claim 33 wherein said user signalsemploy TDMA protocols.
 35. The communication system of claim 33 whereinsaid user signals employ CDMA protocols.
 36. The communication system ofclaim 33 wherein said user signals employ SDMA protocols.
 37. Thecommunication system of claim 33 wherein said user signals employ FDMAprotocols.
 38. In a communication system having a plurality of channels,having a plurality of users for transmitting user signals in userchannels, and having a plurality of macro-diverse collector meansdistributed at macro-diverse locations, the method comprising:for eachof said collector means,receiving said user signals and providing aplurality of received signals for each of said plurality of users,processing said received signals to form collector signals includingsequences of data bits representing the received signals and includinginitial confidence metrics corresponding to said data bits for each ofsaid plurality of users, where the initial confidence metrics arerepresented by an initial number of metric bits,said processingincluding collector confidence metric processing for processing saidinitial confidence metrics to form processed confidence metrics havingbandwidth values, combining said collector signals using said processedconfidence metrics from said plurality of macro-diverse collector meansfor each of said plurality of users to form a final sequence of databits representing the user signals for each of said plurality of users,controlling said bandwidth values.